34 Nlp Engineer jobs in Qatar

SWATX is seeking a highly skilled and experienced Data Science Manager to lead our growing data science team. In this strategic role, you will be responsible for overseeing the development and implementation of data-driven solutions to solve complex business challenges. You will mentor and guide a team of data scientists, driving innovation and excellence in analytics and machine learning. If you are a strong leader with a passion for data science and a proven track record of delivering impactful solutions, we invite you to join us.

Responsibilities:

Lead and mentor a team of data scientists, providing guidance on best practices in data analysis, machine learning, and statistical modeling Develop and execute the data science strategy aligned with business objectives, ensuring that data-driven insights are integrated into decision-making processes Oversee the design and implementation of innovative data science projects that drive value for the organization Collaborate with cross-functional teams to identify opportunities for leveraging data to improve products, services, and operational efficiency Build and maintain strong relationships with stakeholders, understanding their data needs and ensuring timely delivery of insights Monitor and evaluate the performance of data science models and adjust strategies as necessary to achieve desired results Promote a data-driven culture within the organization by communicating the value of data science initiatives to stakeholders at all levels Stay updated on the latest trends and developments in data science and analytics, and integrate new methodologies and tools as appropriate

Requirements

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field Proven experience in a data science role, with at least 5+ years of experience, including 2+ years in a managerial or leadership position Strong proficiency in programming languages such as Python, R, and experience with data manipulation and analysis libraries Solid understanding of machine learning algorithms, statistical methodologies, and data modeling techniques Experience with data visualization tools (e.g., Tableau, Power BI) to communicate findings effectively Excellent project management skills and ability to prioritize tasks in a fast-paced environment Strong analytical and problem-solving skills with attention to detail Exceptional communication skills, both verbal and written, in English and Arabic Proven capability to drive collaboration across teams and influence senior stakeholders

Preferable Certificates:

Certified Data Scientist (CDS) Microsoft Certified: Azure Data Scientist Associate Google Cloud Professional Data Engineer

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SWATX is looking for a visionary and results-driven Senior Data Science Manager to join our leadership team. In this pivotal role, you will be responsible for overseeing the strategic direction and execution of data science initiatives across the organization. You will lead a talented team of data scientists, driving innovation in predictive modeling, machine learning, and advanced analytics. As a key contributor to our data strategy, you will collaborate closely with senior leadership and cross-functional teams to deliver impactful insights and solutions that enhance business performance.

Responsibilities:

1. Develop and implement the overall data science vision, strategy, and framework to align with organizational goals.
2. Lead a high-performing team of data scientists, fostering a culture of collaboration, innovation, and continuous learning.
3. Drive the execution of strategic data science projects, ensuring alignment with business objectives and delivery of actionable insights.
4. Collaborate with stakeholders to identify high-impact opportunities for modeling and analytics that can enhance decision-making and operational efficiency.
5. Oversee the design and implementation of complex machine learning algorithms and statistical models to solve business challenges.
6. Monitor industry trends and emerging technologies in data science and analytics, incorporating best practices into the team’s methodologies.
7. Provide mentorship and professional development opportunities for team members to enhance their skill sets and career growth.
8. Present findings and recommendations to senior leadership, translating complex data insights into clear and actionable strategies.

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SWATX is looking for a visionary and results-driven Senior Data Science Manager to join our leadership team. In this pivotal role, you will be responsible for overseeing the strategic direction and execution of data science initiatives across the organization. You will lead a talented team of data scientists, driving innovation in predictive modeling, machine learning, and advanced analytics. As a key contributor to our data strategy, you will collaborate closely with senior leadership and cross-functional teams to deliver impactful insights and solutions that enhance business performance.

Responsibilities: Develop and implement the overall data science vision, strategy, and framework to align with organizational goals. Lead a high-performing team of data scientists, fostering a culture of collaboration, innovation, and continuous learning. Drive the execution of strategic data science projects, ensuring alignment with business objectives and delivery of actionable insights. Collaborate with stakeholders to identify high-impact opportunities for modeling and analytics that can enhance decision-making and operational efficiency. Oversee the design and implementation of complex machine learning algorithms and statistical models to solve business challenges. Monitor industry trends and emerging technologies in data science and analytics, incorporating best practices into the team’s methodologies. Provide mentorship and professional development opportunities for team members to enhance their skill sets and career growth. Present findings and recommendations to senior leadership, translating complex data insights into clear and actionable strategies.

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About QNB

Established in 1964 as the countrys first Qatari-owned commercial bank, QNB Group has steadily grown to become the largest bank in the Middle East and Africa (MEA) region.

QNB Groups presence through its subsidiaries and associate companies extends to more than 31 countries across three continents providing a comprehensive range of advanced products and services. The total number of employees is more than 28,000 serving up to 20 million customers operating through 1,000 locations, with an ATM network of 4,300 machines.

QNB has maintained its position as one of the highest rated regional banks from leading credit rating agencies including Standard & Poors (A), Moodys (Aa3) and Fitch (A+). The Bank has also been the recipient of many awards from leading international specialised financial publications.

Based on the Groups consistent strong financial performance and its expanding international presence, QNB currently ranks as the most valuable bank brand in the Middle East and Africa, according to Brand Finance Magazine.

QNB Group has an active community support program and sponsors various social, educational and sporting events.

Job Summary

The Senior Vice President (SVP), Data Science, is a strategic leadership role responsible for shaping, leading, and executing QNB&aposs bank-wide Data & AI strategy. This position drives innovation and transformation across the bank using advanced data analytics, machine learning, deep learning, and Generative AI (GenAI). The SVP works closely with executive stakeholders to align data science initiatives with business priorities, ensure strong governance, and build scalable AI capabilities that drive financial performance, operational efficiency, and superior customer experiences. The role also includes oversight of Advanced Analytics, AI model lifecycle management, talent development, and the promotion of ethical Data & AI use across QNB.

Main Responsibilities

• Shareholder & Financial:
• Define and drive execution of QNB&aposs enterprise Data Science & AI strategy aligned to business outcomes.
• Deliver high-impact, AI-powered solutions that generate measurable financial benefits (e.g., revenue growth, cost efficiency, risk mitigation).
• Oversee budgeting and resource allocation across strategic data initiatives.
• Monitor the ROI of Data Science & AI investments using business-focused KPIs and OKRs.
• Establish a data-driven culture across the bank, ensuring AI is embedded in all relevant decision-making processes.
• Implements KPIs and best practices for Senior Vice President, Data Science
• Promote cost consciousness and efficiency and enhance productivity, to minimise cost, avoid waste, and optimise benefits for the bank.
• Act within the limits of the powers delegated to the incumbent and delegate authority to the respective staff and monitor exercise of the same.
• Demonstrate clear understanding of the important factors behind the bank&aposs financial & non-financial performance.
• Customer (Internal & External):
• Partner with Group business Heads and IT to develop AI solutions that enhance customer engagement, improve
  
  

product personalization, and streamline operations.

• Provide thought leadership on the application of GenAI, advanced analytics, and predictive models for business growth.
• Translate complex data science approaches into business-ready narratives for CXOs and Board-level communication.
• Lead AI capability-building programs for business units, enabling self-serve analytics and citizen data science.
• Champion customer-centric design in all AI and data-driven solutions.
• To assist customers in all their queries on Banks product and seek solution to their requests.
• Maintain activities in accordance with Service Level Agreements (SLAs) with internal departments/units to achieve improvements in turn-around time.
• Build and maintain strong/effective relationships with related departments/units to achieve the Groups objectives.
• Provide timely/accurate data to external/internal Auditors, Compliance, Financial Control and Risk when required.
• Internal (Processes, Products, Regulatory):
• Establish scalable AI & ML development pipelines including robust model governance, MLOps, and monitoring frameworks.
• Oversee the development of AI models across use cases such as credit risk, client profitability, fraud detection, customer acquisition, and treasury optimization.
• Ensure compliance with internal and external data protection, governance, and regulatory standards.
• Build and institutionalize reusable data products and GenAI agents across business functions.
• Drive innovation in data science practices by integrating cloud-native platforms, LLMs, and enterprise AI tools.
• Continuous Improvement:
• Set examples by leading improvement initiatives through cross-functional teams ensuring successes.
• Identify and encourage people to adopt practices better than the industry standard.
• Continuously encourage and recognise the importance of thinking out-of-the-box within the team.
• Encourage, solicit and reward innovative ideas even in day-to-day issues.
• Learning & Knowledge:
• Lead a high-performing Data Science & AI team, fostering a culture of experimentation, continuous learning, and ethical AI usage.
• Institutionalize knowledge-sharing platforms and AI Centers of Excellence (CoEs).
• Stay abreast of global AI trends, regulatory developments, and advancements in GenAI, LLMs, and deep learning.
• Collaborate with academia, research bodies, and vendors to infuse cutting-edge knowledge into QNB.
• Proactively identify areas for professional development of self and undertake development activities.
• Seek out opportunities to stay current with advancements in AI and data analytics fields.
• Initiate regular meetings within the Application Development department focused on discussing progress, resolving issues, and addressing concerns related to AI and data analytics projects.
• Hold meetings with staff and assess their performance and your teams overall performance on a regular basis.
• Take decisive action to ensure speedy resolution of unresolved grievances or conflicts within the team members.
• Identify development opportunities and activities for staff and facilitate/coach them to improve their effectives and prepare them to assume greater responsibilities.
• Legal, Regulatory, and Risk Framework Responsibilities:
• Ensure adherence to all AI-related legal, ethical, and compliance frameworks including AI governance, data privacy, and explainability standards.
• Represent Data Science & AI in Operational Risk, Compliance, and Board-level risk reviews.
• Lead remediation planning for model risk, bias detection, and audit compliance.
• Maintain AI documentation in line with regulatory expectations, particularly for credit, fraud, AML, and client fairness.
• Complete all mandatory training provided by the organization to achieve and maintain the required levels of competence in data science, analytics, and AI fields.
• Attend all required (internal and external) seminars and workshops, as instructed, to stay abreast of the latest advancements and best practices in data analytics and AI.
• Other:
• Ensure high standards of data protection and confidentiality to safeguard all data and systems.
• Maintaining utmost confidentiality concerning customer data and internal information obtained during the course of business and provide such information on a need-to-know basis only to Senior Management, Audit and Compliance functions, and relevant Regulators.
• Maintain high professional standards to uphold the organization&aposs reputation and to strengthen its leadership position in data analytics and AI.
• All other ad hoc duties/activities related to data analytics and AI that management might request from time to time
  
  

Education And Experience Requirements

• Masters or PhD in Data Science, Computer Science, AI, Engineering, Statistics, or related quantitative field.
• Minimum 15 years of total experience, with at least 10 years in data analytics, data science, or AI leadership roles.
• Proven experience leading AI transformation programs in banking or financial services.
• Deep expertise in AI/ML techniques including LLMs, deep learning, predictive analytics, GenAI, and NLP.
• Strong track record of building and scaling AI teams and delivering enterprise-grade AI solutions.
• Solid knowledge of financial products, customer analytics, credit scoring, risk modeling, and regulatory AI applications.
• Hands-on experience with cloud ecosystems (Azure, AWS, GCP), modern data stacks, and production-grade ML/AI platforms.
• Strong stakeholder management and strategic execution and advisory skills.
• Ability to design AI governance frameworks aligned with regulatory and ethical standards.
• Advanced skills in Python, Spark, SQL, cloud-based ML pipelines, MLOps, and LLM deployment.
• Familiarity with tools like Databricks, Azure AI, Dataiku, and enterprise GenAI platforms.
• Clear communication of complex data science topics to non-technical audiences.
• Demonstrated innovation mindset with bias for action and delivery.
  
  

Note: you will be required to attach the following:

• Resume/CV
• Copy of Passport or QID
• Copy of Education Certificate

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About QNB

Established in 1964 as the countrys first Qatari-owned commercial bank, QNB Group has steadily grown to become the largest bank in the Middle East and Africa (MEA) region.

QNB Groups presence through its subsidiaries and associate companies extends to more than 31 countries across three continents providing a comprehensive range of advanced products and services. The total number of employees is more than 28,000 serving up to 20 million customers operating through 1,000 locations, with an ATM network of 4,300 machines.

QNB has maintained its position as one of the highest rated regional banks from leading credit rating agencies including Standard & Poors (A), Moodys (Aa3) and Fitch (A+). The Bank has also been the recipient of many awards from leading international specialised financial publications.

Based on the Groups consistent strong financial performance and its expanding international presence, QNB currently ranks as the most valuable bank brand in the Middle East and Africa, according to Brand Finance Magazine.

QNB Group has an active community support program and sponsors various social, educational and sporting events.

Job Summary

The Senior Vice President (SVP), Data Science, is a strategic leadership role responsible for shaping, leading, and executing QNB&aposs bank-wide Data & AI strategy. This position drives innovation and transformation across the bank using advanced data analytics, machine learning, deep learning, and Generative AI (GenAI). The SVP works closely with executive stakeholders to align data science initiatives with business priorities, ensure strong governance, and build scalable AI capabilities that drive financial performance, operational efficiency, and superior customer experiences. The role also includes oversight of Advanced Analytics, AI model lifecycle management, talent development, and the promotion of ethical Data & AI use across QNB.

Main Responsibilities

Shareholder & Financial: Define and drive execution of QNB&aposs enterprise Data Science & AI strategy aligned to business outcomes. Deliver high-impact, AI-powered solutions that generate measurable financial benefits (e.g., revenue growth, cost efficiency, risk mitigation). Oversee budgeting and resource allocation across strategic data initiatives. Monitor the ROI of Data Science & AI investments using business-focused KPIs and OKRs. Establish a data-driven culture across the bank, ensuring AI is embedded in all relevant decision-making processes. Implements KPIs and best practices for Senior Vice President, Data Science Promote cost consciousness and efficiency and enhance productivity, to minimise cost, avoid waste, and optimise benefits for the bank. Act within the limits of the powers delegated to the incumbent and delegate authority to the respective staff and monitor exercise of the same. Demonstrate clear understanding of the important factors behind the bank&aposs financial & non-financial performance. Customer (Internal & External): Partner with Group business Heads and IT to develop AI solutions that enhance customer engagement, improve

product personalization, and streamline operations.

Provide thought leadership on the application of GenAI, advanced analytics, and predictive models for business growth. Translate complex data science approaches into business-ready narratives for CXOs and Board-level communication. Lead AI capability-building programs for business units, enabling self-serve analytics and citizen data science. Champion customer-centric design in all AI and data-driven solutions. To assist customers in all their queries on Banks product and seek solution to their requests. Maintain activities in accordance with Service Level Agreements (SLAs) with internal departments/units to achieve improvements in turn-around time. Build and maintain strong/effective relationships with related departments/units to achieve the Groups objectives. Provide timely/accurate data to external/internal Auditors, Compliance, Financial Control and Risk when required. Internal (Processes, Products, Regulatory): Establish scalable AI & ML development pipelines including robust model governance, MLOps, and monitoring frameworks. Oversee the development of AI models across use cases such as credit risk, client profitability, fraud detection, customer acquisition, and treasury optimization. Ensure compliance with internal and external data protection, governance, and regulatory standards. Build and institutionalize reusable data products and GenAI agents across business functions. Drive innovation in data science practices by integrating cloud-native platforms, LLMs, and enterprise AI tools. Continuous Improvement: Set examples by leading improvement initiatives through cross-functional teams ensuring successes. Identify and encourage people to adopt practices better than the industry standard. Continuously encourage and recognise the importance of thinking out-of-the-box within the team. Encourage, solicit and reward innovative ideas even in day-to-day issues. Learning & Knowledge: Lead a high-performing Data Science & AI team, fostering a culture of experimentation, continuous learning, and ethical AI usage. Institutionalize knowledge-sharing platforms and AI Centers of Excellence (CoEs). Stay abreast of global AI trends, regulatory developments, and advancements in GenAI, LLMs, and deep learning. Collaborate with academia, research bodies, and vendors to infuse cutting-edge knowledge into QNB. Proactively identify areas for professional development of self and undertake development activities. Seek out opportunities to stay current with advancements in AI and data analytics fields. Initiate regular meetings within the Application Development department focused on discussing progress, resolving issues, and addressing concerns related to AI and data analytics projects. Hold meetings with staff and assess their performance and your teams overall performance on a regular basis. Take decisive action to ensure speedy resolution of unresolved grievances or conflicts within the team members. Identify development opportunities and activities for staff and facilitate/coach them to improve their effectives and prepare them to assume greater responsibilities. Legal, Regulatory, and Risk Framework Responsibilities: Ensure adherence to all AI-related legal, ethical, and compliance frameworks including AI governance, data privacy, and explainability standards. Represent Data Science & AI in Operational Risk, Compliance, and Board-level risk reviews. Lead remediation planning for model risk, bias detection, and audit compliance. Maintain AI documentation in line with regulatory expectations, particularly for credit, fraud, AML, and client fairness. Complete all mandatory training provided by the organization to achieve and maintain the required levels of competence in data science, analytics, and AI fields. Attend all required (internal and external) seminars and workshops, as instructed, to stay abreast of the latest advancements and best practices in data analytics and AI. Other: Ensure high standards of data protection and confidentiality to safeguard all data and systems. Maintaining utmost confidentiality concerning customer data and internal information obtained during the course of business and provide such information on a need-to-know basis only to Senior Management, Audit and Compliance functions, and relevant Regulators. Maintain high professional standards to uphold the organization&aposs reputation and to strengthen its leadership position in data analytics and AI. All other ad hoc duties/activities related to data analytics and AI that management might request from time to time

Education And Experience Requirements

Masters or PhD in Data Science, Computer Science, AI, Engineering, Statistics, or related quantitative field. Minimum 15 years of total experience, with at least 10 years in data analytics, data science, or AI leadership roles. Proven experience leading AI transformation programs in banking or financial services. Deep expertise in AI/ML techniques including LLMs, deep learning, predictive analytics, GenAI, and NLP. Strong track record of building and scaling AI teams and delivering enterprise-grade AI solutions. Solid knowledge of financial products, customer analytics, credit scoring, risk modeling, and regulatory AI applications. Hands-on experience with cloud ecosystems (Azure, AWS, GCP), modern data stacks, and production-grade ML/AI platforms. Strong stakeholder management and strategic execution and advisory skills. Ability to design AI governance frameworks aligned with regulatory and ethical standards. Advanced skills in Python, Spark, SQL, cloud-based ML pipelines, MLOps, and LLM deployment. Familiarity with tools like Databricks, Azure AI, Dataiku, and enterprise GenAI platforms. Clear communication of complex data science topics to non-technical audiences. Demonstrated innovation mindset with bias for action and delivery.

Note: you will be required to attach the following:

Resume/CV Copy of Passport or QID Copy of Education Certificate Show more

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We are Qatar Insurance Company (QIC), the leading insurance provider in the GCC. With a history dating back to 1964, we have established ourselves as a pioneer in the insurance industry, offering innovative solutions to meet the diverse needs of individuals and businesses.

Our vision is to make QIC group the first Digital Ecosystem in the region by combining insurance and non-insurance services on a single platform. Through our digital platforms, such as qic.online and the QIC app, we empower customers to manage their needs anytime and anywhere.

Our employees have been featured in Forbes 30 under 30, teach at online universities, serve on program committees of major IT conferences, and have previously worked at Yandex, Tinkoff, Avito, Ozon, and other leading tech companies.

About the position

We are looking for an experienced AI/ML Engineer to join our team and help design, build, and scale intelligent systems that power real business solutions. You will work across LLMs, Computer Vision, Speech AI, and AI Infrastructure, embedding advanced AI into core business processes and client-facing products.

Responsibilities

• Build chatbots, RAG systems, and automated document processing pipelines involving LLM development.
• Implement OCR for insurance documents, damage assessment from photos, and identity verification using Computer Vision techniques.
• Develop transcription, voice analytics, and multilingual support solutions in Speech AI.
• Deploy and monitor AI models, and integrate them with cloud AI services as part of AI Infrastructure.
• Embed AI into business workflows, create AI APIs, and design user-friendly AI-powered experiences for products.

Requirements

• At least 3 years of experience in AI/ML engineering with a focus on production systems.
• Strong Python skills (advanced) and experience with FastAPI/Flask for API development.
• Hands-on experience with LLM tools such as OpenAI API, LangChain, Hugging Face Transformers.
• Proficiency in deep learning frameworks like PyTorch or TensorFlow for fine-tuning models.
• Experience with Docker & Kubernetes for containerization and orchestration of AI applications.

Core AI/ML Competencies

• Prompt Engineering: designing effective prompts for LLMs.
• Fine-tuning: adapting pre-trained models to specific business tasks.
• Retrieval-Augmented Generation (RAG): working with vector databases and embeddings.
• Computer Vision Pipelines: from preprocessing to inference.
• Multimodal AI: building solutions that combine text and images.

What We Offer

• Long-term service agreement with QIC.
• A diverse remote team working from 25 different countries.
• Monthly salary paid in US dollars via SWIFT bank transfer.
• Full-time remote work, Sunday to Thursday, 5 days per week.
• Vacation policy aligned with Qatar holidays, including 20 workdays of vacation and 10 sick days.
• Biannual performance reviews with potential raises in March and September.
• Potential opportunity for Qatar ID and relocation to Doha, Qatar.

Quality healthcare with up to $1,500 dental coverage, regardless of your location.

Additional Benefits

• Language classes to improve communication skills in English, Arabic, or other languages.
• Mental health support services, including Yasno, with 70% coverage, plus 3 mental health days annually.
• Guidance on local and international tax regulations.
• $600/year support for further courses and internal workshops.
• Join our QIC running club for motivation, coaching, and marathon support.
• Salary payouts in USD, EUR, or AED, based on your preference.
• Extra paid leave, including vacation days, sick leave, and bonus days for longevity.

Technologies

We are open to adopting new stacks and technologies to build market-leading solutions.

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time left to apply End Date: August 29, 2025 (3 days left to apply)

job requisition id 2023617

We are hiring AI Engineer in our Qatar campus.

The AI Engineer will serve as a core member of the Computing Services team, responsible for designing, developing, supporting, and deploying AI-driven solutions that advance the campus’ academic, research, and administrative missions. This role combines strong technical expertise with excellent communication, documentation, and training skills. The AI Engineer will also lead training initiatives to foster AI adoption and promote the responsible, ethical, and innovative use of AI technologies across the campus community.

Key Responsibilities

AI Development, Support & Deployment (50%)

Serve as a primary support resource for the AI service catalog by addressing inquiries, troubleshooting issues, and ensuring timely resolution in collaboration with technical teams.

Maintain, support, and continuously improve existing AI tools and services used by faculty, staff, and students.

Design and implement AI solutions using Python and standard frameworks such as scikit-learn, PyTorch, and TensorFlow.

Develop and deploy AI services that integrate with both on-premise and cloud infrastructure.

Leverage experience with AI/ML solutions in Azure, AWS, or Google Cloud environments to support scalable deployments.

Partner with IT security and data governance teams to ensure AI solutions comply with institutional standards, research data policies (e.g., FERPA), and ethical AI guidelines

Training, Stakeholder Engagement & Documentation (30%)

Design and deliver engaging AI workshops tailored to faculty, staff, and students to build AI literacy, awareness, and practical application skills.

Create clear and actionable training materials, guides, and documentation that empower campus stakeholders to co-develop and utilize AI solutions.

Maintain a comprehensive, user-friendly repository of AI architectures, workflows, project documentation, and educational resources.

Research, Innovation & Technology Evaluation (10%)

Stay up to date on emerging AI trends, frameworks, and cloud services, particularly those relevant to higher education and academic research.

Evaluate and recommend new tools, platforms, and frameworks to support instructional innovation, research computing, and operational effectiveness.

Identify and explore new AI use cases on campus; contribute to ideation pipelines, pilot initiatives, and early-stage implementations.

Work closely with faculty, researchers, staff, and students to understand institutional needs and co-design AI-powered solutions.

Cultivate and maintain strong relationships with key stakeholders, vendors, and colleagues across departments and the university’s main campus.

Minimum Qualifications

Education:

Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field is required.

Experience:

3–5 years of hands-on experience in AI/ML engineering, software development, or cloud-based solution delivery.

Proficiency in Python and libraries such as NumPy, Pandas, scikit-learn, TensorFlow, or PyTorch.

Experience deploying AI/ML solutions in Azure, AWS, or Google Cloud environments .

Strong ability to communicate technical concepts clearly to both technical and non-technical audiences.

Excellent presentation, documentation, and training facilitation skills.

Joining the CMU team opens the door to an array of exceptional benefits.

For a comprehensive overview of the benefits available, explore our Benefits page .

At Carnegie Mellon, we value the whole package when extending offers of employment. Beyond credentials, we evaluate the role and responsibilities, your valuable work experience, and the knowledge gained through education and training. We appreciate your unique skills and the perspective you bring. Your journey with us is about more than just a job; it’s about finding the perfect fit for your professional growth and personal aspirations.

Are you interested in an exciting opportunity with an exceptional organization! Apply today!

Location

Doha, Qatar

Job Function

We are hiring AI Engineer in our Qatar campus.

The AI Engineer will serve as a core member of the Computing Services team, responsible for designing, developing, supporting, and deploying AI-driven solutions that advance the campus’ academic, research, and administrative missions. This role combines strong technical expertise with excellent communication, documentation, and training skills. The AI Engineer will also lead training initiatives to foster AI adoption and promote the responsible, ethical, and innovative use of AI technologies across the campus community.

Key Responsibilities

AI Development, Support & Deployment (50%)

Serve as a primary support resource for the AI service catalog by addressing inquiries, troubleshooting issues, and ensuring timely resolution in collaboration with technical teams.

Maintain, support, and continuously improve existing AI tools and services used by faculty, staff, and students.

Design and implement AI solutions using Python and standard frameworks such as scikit-learn, PyTorch, and TensorFlow.

Develop and deploy AI services that integrate with both on-premise and cloud infrastructure.

Leverage experience with AI/ML solutions in Azure, AWS, or Google Cloud environments to support scalable deployments.

Partner with IT security and data governance teams to ensure AI solutions comply with institutional standards, research data policies (e.g., FERPA), and ethical AI guidelines

Training, Stakeholder Engagement & Documentation (30%)

Design and deliver engaging AI workshops tailored to faculty, staff, and students to build AI literacy, awareness, and practical application skills.

Create clear and actionable training materials, guides, and documentation that empower campus stakeholders to co-develop and utilize AI solutions.

Maintain a comprehensive, user-friendly repository of AI architectures, workflows, project documentation, and educational resources.

Research, Innovation & Technology Evaluation (10%)

Stay up to date on emerging AI trends, frameworks, and cloud services, particularly those relevant to higher education and academic research.

Evaluate and recommend new tools, platforms, and frameworks to support instructional innovation, research computing, and operational effectiveness.

Identify and explore new AI use cases on campus; contribute to ideation pipelines, pilot initiatives, and early-stage implementations.

Collaboration (10%)

Work closely with faculty, researchers, staff, and students to understand institutional needs and co-design AI-powered solutions.

Cultivate and maintain strong relationships with key stakeholders, vendors, and colleagues across departments and the university’s main campus.

Minimum Qualifications

Education:

Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field is required.

Master’s degree preferred.

Experience:

3–5 years of hands-on experience in AI/ML engineering, software development, or cloud-based solution delivery.

Proficiency in Python and libraries such as NumPy, Pandas, scikit-learn, TensorFlow, or PyTorch.

Experience deploying AI/ML solutions in Azure, AWS, or Google Cloud environments .

Skills & Competencies:

Strong ability to communicate technical concepts clearly to both technical and non-technical audiences.

Excellent presentation, documentation, and training facilitation skills.

Joining the CMU team opens the door to an array of exceptional benefits.

Benefits eligible employees enjoy a wide array of benefits including comprehensive medical, prescription, dental, and vision insurance as well as a generous retirement savings program with employer contributions. Unlock your potential with tuition benefits , take well-deserved breaks with ample paid time off and observed holidays , and rest easy with life and accidental death and disability insurance.

Additional perks include a free Pittsburgh Regional Transit bus pass, access to our Family Concierge Team to help navigate childcare needs, fitness center access , and much more!

For a comprehensive overview of the benefits available, explore our Benefits page .

At Carnegie Mellon, we value the whole package when extending offers of employment. Beyond credentials, we evaluate the role and responsibilities, your valuable work experience, and the knowledge gained through education and training. We appreciate your unique skills and the perspective you bring. Your journey with us is about more than just a job; it’s about finding the perfect fit for your professional growth and personal aspirations.

Are you interested in an exciting opportunity with an exceptional organization! Apply today!

Location

Doha, Qatar

Job Function

Software/Applications Development/Engineering

Position Type

Staff – Fixed Term (Fixed Term)

Full Time/Part time

Full time

Pay Basis

More Information:

• Please visit “Why Carnegie Mellon ” to learn more about becoming part of an institution inspiring innovations that change the world.

• Click here to view a listing of employee benefits

• Carnegie Mellon University is an Equal Opportunity Employer/Disability/Veteran .

• Statement of Assurance

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About Us

Mathspace is on a mission to transform mathematics education. We believe that every student can learn and grow in mathematics with the right support—and we're building the most intelligent, adaptive platform to make that possible.

For over a decade, we've pioneered interactive, feedback-driven math learning experiences used by hundreds of thousands of students and teachers globally. But we're just getting started.

The future of math education is one where AI helps every learner receive personalized, real-time guidance—just like a tutor would. And we're building it.

We're a passionate, mission-driven team that blends deep educational insight with cutting-edge technology. At Mathspace, your work directly impacts how the next generation learns.

About The Role

As an AI Product Engineer at Mathspace, you'll lead the development of intelligent learning experiences powered by large language models (LLMs) and other forms of generative AI. From concept to production, you'll build novel product features that help students get timely hints, conversational feedback, and human-like math support—at scale.

You'll join a cross-functional product squad of engineers, designers, educators, and product managers, and work across the stack to explore what's possible at the intersection of pedagogy and AI. You'll evaluate models, design prompts and evaluation frameworks, and help us ship polished experiences to classrooms around the world.

We're still in the early days of our AI journey, and you'll be a key contributor in shaping our strategy, systems, and culture around building with LLMs.

What You'll Be Doing

• Designing and building AI-powered learning experiences that integrate LLMs into Mathspace's student and teacher-facing apps.
• Prototyping, testing, and deploying LLM-based features, such as math-specific feedback, adaptive hints, automated question generation, and teacher co-pilot tools.
• Working across the stack using React, TypeScript, Python and GraphQL.
• Experimenting with prompting, RAG, vector search, and fine-tuning strategies to optimize for student learning outcomes.
• Collaborating with our curriculum and pedagogy teams to ensure our AI experiences are pedagogically sound and aligned with our educational values.
• Contributing to our AI infra and LLMOps processes, including evaluation pipelines, prompt versioning, and observability tools.
• Thinking creatively and critically about what LLMs should and shouldn't do in an educational context—and designing safeguards accordingly.
  
  

Requirements

What We're Looking For

• 5+ years of industry experience in product-focused full stack or backend engineering.
• Proficiency in our stack: React/TypeScript, Python, GraphQL.
• Hands-on experience building and deploying LLM-powered applications in production.
• Familiarity with tools and concepts like RAG, prompt engineering, evaluation frameworks, and LLMOps best practices.
• A strong sense of product intuition and user empathy, especially in educational contexts.
• Excellent communication and collaboration skills. You'll be working cross-functionally with teams across pedagogy, design, and engineering.
• A desire to move fast, learn continuously, and build things that really matter for students and teachers
  
  

Benefits

Why Join Mathspace?

• Mission-driven work: Help reimagine math education for students and teachers everywhere.
• Meaningful scale: Your work will reach hundreds of thousands of learners across Australia, the US, and beyond.
• Small team, big impact: We're a lean, high-trust team where individual ownership matters.
• Flexible work: We support remote work with some timezone overlap with Sydney. Our HQ is near Central Station.
• Support for growth: We offer a yearly stipend for training and professional development.
• Do good beyond product: We partner with pledge1percent.org and offer 2.5 paid volunteer days annually.
• Competitive salary and equipment: Including a MacBook Pro and any peripherals you need to do your best work

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The AI Ops Engineer manages thedeployment, monitoring, and maintenance of AI models. This role involvesensuring the reliability, scalability, and performance of AI systems,collaborating with cross-functional teams to optimize AI operations, and troubleshootingissues as they arise.

Responsibilities and Duties

• Deploy,monitor, and maintain AI models and systems to ensure optimal performance andreliability.
• Implementand manage CI/CD pipelines for the continuous integration and delivery of AImodels.
• Collaboratewith data scientists, AI engineers, and other stakeholders to understand modelrequirements and ensure successful deployment.
• Monitorthe performance of AI models and systems, identifying and resolving issuespromptly.
• Developand maintain automated monitoring and alerting systems to ensure the health andperformance of AI systems.
• OptimizeAI models and infrastructure for scalability and efficiency
• Ensurecompliance with data governance, security, and regulatory standards in AIoperations.
• Documentdeployment procedures, monitoring processes, and maintenance activities.
• Stayupdated with the latest advancements in AI operations and infrastructuretechnologies.
• Providetechnical support and guidance to junior team members.
• Participatein project planning and contribute to the development of project timelines anddeliverables.
• Performother duties relevant to the job as assigned by the Sr. AI Ops Engineer orsenior management.

Requirements

• Bachelor’sdegree in Computer Science, Information Technology, or a related field
• Relevantcertifications (e.g., AWS Certified DevOps Engineer, Google Cloud ProfessionalDevOps Engineer) are preferred
• Minimumof 3 years of experience in AI operations, DevOps, or related fields
• Experiencein managing the deployment and maintenance of AI models
• Strongprogramming skills in languages such as Python
• Proficiency in AI and machinelearning frameworks (e.g., TensorFlow, PyTorch)
• Experience with CI/CD tools (e.g.,Jenkins, GitLab CI)
• Excellent problem-solving andtroubleshooting skills
• Strongcommunication and interpersonal skills
• In-depthknowledge of AI operations and infrastructure management
• Familiarity with cloud platforms(e.g., AWS, Azure, Google Cloud) and their AI services
• Understandingof data governance, security, and regulatory standards
• Ability tomanage multiple tasks and prioritize effectively
• Strong attention to detail andcommitment to delivering high-quality work
• Abilityto work independently and as part of a team
• Programminglanguages (e.g., Python)
• AI and machine learning frameworks(e.g., TensorFlow, PyTorch)
• CI/CD tools (e.g., Jenkins, GitLabCI)
• Monitoring and logging tools (e.g.,Prometheus, ELK Stack)
• Collaborationand communication tools (e.g., Slack, Microsoft Teams)
  

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