22 Healthcare AI jobs in Qatar

Role & responsibilities

We are seeking a dynamic and highly motivated AI Business Development Manager who will play a pivotal role in driving AI-led digital transformation for our clients. This role demands a unique blend of business acumen, customer engagement, and deep understanding of the latest trends in Artificial Intelligence (AI), Machine Learning (ML), and Data Science.

The ideal candidate will engage directly with enterprise and government customers to understand their business challenges, identify opportunities for AI intervention, and translate those into high-impact, real-world AI solutions and use cases.

Customer Engagement & Opportunity Discovery

• Meet with key stakeholders across industries to understand their business models, challenges, and pain points.
• Conduct detailed needs assessments to uncover process inefficiencies, gaps, and areas where AI can drive measurable value.
• Act as a trusted advisor to CXOs, department heads, and technical decision-makers on AI adoption.

Use Case Ideation & Solutioning

• Co-create and develop AI-driven use cases tailored to customer-specific problems (e.g., predictive analytics, computer vision, NLP, generative AI).
• Collaborate with AI architects and data science teams to evaluate feasibility and scope of solutions.
• Translate business requirements into technical solution briefs, PoC proposals, and value propositions.

Business Development & Go-to-Market Execution

• Own and drive the AI sales funnel from lead generation to deal closure.
• Collaborate with cross-functional teams (Sales, Pre-Sales, Product, Delivery) to develop proposals, RFIs/RFPs, and pricing models.
• Prepare compelling presentations and demos to articulate the power of AI solutions in solving business problems.

Market & Trend Intelligence

• Stay abreast of the latest AI/ML trends, emerging technologies (e.g., GenAI, LLMs, Edge AI), and industry benchmarks.
• Continuously scout the market for innovative AI use cases and competitor activities.
• Provide strategic inputs for refining our AI portfolio, industry focus, and solution roadmap.

Qualifications

• Bachelor's or Master's degree in Business, Computer Science, Data Science, or related field.
• 5+ years of experience in business development, solution consulting, or customer-facing AI roles.
• Proven experience in identifying and converting AI/Data opportunities into revenue-generating projects.
• Strong understanding of AI technologies: Generative AI, LLMs, ML Ops, NLP, Computer Vision, Predictive Modeling, etc.
• Excellent communication, storytelling, and presentation skills.
• Ability to engage both technical and non-technical stakeholders with equal ease.

Preferred Skills

• Knowledge/Experience working with platforms like Azure AI, Dataiku, or C3 AI, Cohere, Open Source AI frameworks and Data platforms like Cloudera, Snowflake etc.
• Knowledge of industry-specific AI applications in sectors like healthcare, finance, manufacturing, public sector, etc. is very important.
• Prior experience in a consulting, IT services, or AI-focused organization is a strong plus.

We are seeking a dynamic and highly motivated AI Business Development Manager who will play a pivotal role in driving AI-led digital transformation for our clients. This role demands a unique blend of business acumen, customer engagement, and deep understanding of the latest trends in Artificial Intelligence (AI), Machine Learning (ML), and Data Science.

The ideal candidate will engage directly with enterprise and government customers to understand their business challenges, identify opportunities for AI intervention, and translate those into high-impact, real-world AI solutions and use cases.

Key Responsibilities

Customer Engagement & Opportunity Discovery

• Meet with key stakeholders across industries to understand their business models, challenges, and pain points.

• Conduct detailed needs assessments to uncover process inefficiencies, gaps, and areas where AI can drive measurable value.

• Act as a trusted advisor to CXOs, department heads, and technical decision-makers on AI adoption.

Use Case Ideation & Solutioning

• Co-create and develop AI-driven use cases tailored to customer-specific problems (e.g., predictive analytics, computer vision, NLP, generative AI).

• Collaborate with AI architects and data science teams to evaluate feasibility and scope of solutions.

• Translate business requirements into technical solution briefs, PoC proposals, and value propositions.

Business Development & Go-to-Market Execution

• Own and drive the AI sales funnel — from lead generation to deal closure.

• Collaborate with cross-functional teams (Sales, Pre-Sales, Product, Delivery) to develop proposals, RFIs/RFPs, and pricing models.

• Prepare compelling presentations and demos to articulate the power of AI solutions in solving business problems.

Market & Trend Intelligence

• Stay abreast of the latest AI/ML trends, emerging technologies (e.g., GenAI, LLMs, Edge AI), and industry benchmarks.

• Continuously scout the market for innovative AI use cases and competitor activities.

• Provide strategic inputs for refining our AI portfolio, industry focus, and solution roadmap.

Qualifications

• Bachelor's or Master's degree in Business, Computer Science, Data Science, or related field.

• 5+ years of experience in business development, solution consulting, or customer-facing AI roles.

• Proven experience in identifying and converting AI/Data opportunities into revenue-generating projects.

• Strong understanding of AI technologies: Generative AI, LLMs, ML Ops, NLP, Computer Vision, Predictive Modeling, etc.

• Excellent communication, storytelling, and presentation skills.

• Ability to engage both technical and non-technical stakeholders with equal ease.

Preferred Skills

• Knowledge/Experience working with platforms like Azure AI, Dataiku, or C3 AI, Cohere, Open Source AI frameworks and Data platforms like Cloudera, Snowflake etc.

• Knowledge of industry-specific AI applications in sectors like healthcare, finance, manufacturing, public sector, etc. is very important.

• Prior experience in a consulting, IT services, or AI-focused organization is a strong plus.

Position Summary

We are seeking a dynamic and highly motivated
AI Business Development Manager
who will play a pivotal role in driving AI-led digital transformation for our clients. This role demands a unique blend of business acumen, customer engagement, and deep understanding of the latest trends in
Artificial Intelligence (AI)
,
Machine Learning (ML)
, and
Data Science
.

The ideal candidate will engage directly with enterprise and government customers to understand their business challenges, identify opportunities for AI intervention, and translate those into high-impact, real-world AI solutions and use cases.

Key Responsibilities

Customer Engagement & Opportunity Discovery

• Meet with key stakeholders across industries to
  understand their business models, challenges, and pain points
  .
• Conduct detailed
  needs assessments
  to uncover process inefficiencies, gaps, and areas where AI can drive measurable value.
• Act as a
  trusted advisor
  to CXOs, department heads, and technical decision-makers on AI adoption.

Use Case Ideation & Solutioning

• Co-create and develop AI-driven use cases
  tailored to customer-specific problems (e.g., predictive analytics, computer vision, NLP, generative AI).
• Collaborate with AI architects and data science teams to evaluate feasibility and scope of solutions.
• Translate business requirements into
  technical solution briefs
  , PoC proposals, and value propositions.

Business Development & Go-to-Market Execution

• Own and drive the
  AI sales funnel
  — from lead generation to deal closure.
• Collaborate with cross-functional teams (Sales, Pre-Sales, Product, Delivery) to develop proposals, RFIs/RFPs, and pricing models.
• Prepare compelling
  presentations and demos
  to articulate the power of AI solutions in solving business problems.

Market & Trend Intelligence

• Stay abreast of the
  latest AI/ML trends
  , emerging technologies (e.g., GenAI, LLMs, Edge AI), and industry benchmarks.
• Continuously scout the market for innovative AI use cases and competitor activities.
• Provide strategic inputs for refining our
  AI portfolio, industry focus, and solution roadmap
  .

Qualifications

• Bachelor's or Master's degree in Business, Computer Science, Data Science, or related field.
• 5+ years of experience in
  business development
  ,
  solution consulting
  , or
  customer-facing AI roles
  .
• Proven experience in identifying and converting
  AI/Data opportunities into revenue-generating projects
  .
• Strong understanding of AI technologies:
  Generative AI, LLMs, ML Ops, NLP, Computer Vision, Predictive Modeling
  , etc.
• Excellent communication, storytelling, and presentation skills.
• Ability to engage both
  technical and non-technical stakeholders
  with equal ease.

Preferred Skills

• Knowledge/Experience working with platforms like Azure AI, Dataiku, or C3 AI, Cohere,
  Open Source AI frameworks
  and Data platforms like Cloudera, Snowflake etc.
• Knowledge of
  industry-specific AI applications
  in sectors like healthcare, finance, manufacturing, public sector, etc. is very important.
• Prior experience in a
  consulting, IT services, or AI-focused organization
  is a strong plus.

Apt Resources is seeking an experienced Machine Learning Engineer for a client in Abu Dhabi's Government & Public Sector. In this role, you will design and deploy cutting-edge AI/ML solutions using Large Language Models (LLMs) like GPT, Llama, and BERT to drive innovation in public services.

This is an exciting opportunity to work on high-impact projects involving Retrieval-Augmented Generation (RAG), fine-tuning, and prompt engineering, ensuring secure, scalable, and compliant AI systems for government applications.

• Develop and optimize AI/ML pipelines for LLMs, focusing on RAG architectures, fine-tuning, and prompt engineering tailored for public sector needs.
• Implement scalable solutions using Python, LangChain, HuggingFace, PyTorch/TensorFlow, and cloud-based ML services (Azure ML preferred).
• Integrate vector/graph databases (Weaviate, Neo4j) into production systems to enhance data retrieval and analysis.
• Deploy and monitor models in production, ensuring adherence to government security and compliance standards.
• Collaborate with cross-functional teams to align AI solutions with public sector objectives (e.g., citizen services, data governance, operational efficiency).

• 6-14 years of hands-on experience in AI/ML, with a strong focus on LLMs and GenAI.
• Expertise in LLM architectures (Transformers), prompt engineering, and RAG implementations.
• Proficiency in Python and ML frameworks (LangChain, LlamaIndex, HuggingFace, Scikit-learn).
• Experience with cloud platforms (Azure ML, AWS, or GCP) and MLOps tools (MLflow, model monitoring).
• Familiarity with vector databases, ETL pipelines, and unstructured data handling.
• Knowledge of government IT standards or secure deployments is a plus.

To be discussed

Job Summary
You will be responsible for end-to-end data science cycles, encompassing designing, training, implementing, evaluating, and monitoring machine learning models, and will also design and implement highly scalable tools and algorithms based on state-of-the-art Machine Learning and Deep Learning methodologies.

You will work across the ML stack, from researching models, working with large datasets, training, and tuning existing models to creating new models, deploying them at scale, analyzing results, and presenting findings to stakeholders across tech and business domains.

Job Objectives

• Develop and implement advanced predictive models to optimize customer experiences and other business outcomes.
• Analyze large and complex datasets to extract actionable insights and drive business decisions.
• Interpret results and provide actionable insights to guide real-time decision-making within the business context.
• Collaborate with cross-functional teams to ensure proper deployment and integration of ML models for new releases.

Job Responsibilities
Predictive Modeling and Deployment

• Develop and implement advanced predictive models to forecast key business metrics such as sales, customer churn, or product demand.
• Utilize predictive modeling to optimize customer experiences and other business outcomes.
• Execute machine learning models, algorithms, and statistical techniques to analyze historical data and ensure scalability and efficiency.

Data Preparation and Analysis

• Develop and use advanced software programs, algorithms, and query techniques to cleanse, integrate, and evaluate datasets for model inputs.
• Analyze large and complex datasets to extract actionable insights and identify trends and patterns that can drive business decisions.
• Identify manual human processes, understand user behaviors, and analyze use cases that can be augmented or automated.

Model Deployment and Interpretation

• Deploy models into production environments and monitor their performance over time.
• Apply statistical, mathematical, and predictive modeling techniques to build, maintain, and improve real-time decision systems.
• Interpret results, develop insights within the business context, and provide guidance on risks and limitations

Development & Documentation

• Write the code as per agreed software design rules to keep it aligned with the rest of the code base.
• Code the final implementation that the generated code is referring to.
• Follow company software data protection and security guidelines in developing software.
• Accurately estimate the time needed to complete an assigned task.
• Identify possible causes of issues or problems.
• Think through and recommend solutions when raising issues around code, requirements, etc.
• Write technical design documentation that fully defines all application code.
• Maintain detailed knowledge of iHorizons products and services.
• Understand the business impact for labs outcomes.

Collaboration & Team Guidance

• Stay updated on the latest research, learn new applications, tools, and technologies in the fields of data science and machine learning through intensive and focused effort.
• Collaborate with technical and non-technical business partners to develop analytical dashboards describing ML algorithm findings to stakeholders.
• Collaborate with other teams to perform code reviews and oversee proper deployment for new releases.
• Actively mentor and support mid-level and junior developers in their professional growth.
• Provide guidance on best practices in machine learning, code reviews, and project design.
• Foster an inclusive and collaborative environment that encourages continuous learning and development within the team.
• Oversee interactions with vendors and third-party service providers, including collaborating on the design and implementation of technical architectures, and acting as a point of contact for resolving technical issues. Maintain clear communication with internal stakeholders regarding vendor-related activities, updates, and issues to facilitate smooth collaboration and decision-making processes.

Job Requirements
Educational Qualification

• Bachelor's degree in data science, statistics, and computer science is a MUST.
• Google Cloud - Professional Machine Learning Engineer Certificate
• Google AgentSpace implementation experience

Previous Work Experience

• 3-4+ Years of experience in data science or machine learning.
• Must have strong experience in at least one of the following areas:
• Vision models
• NLP models (Experience in Arabic NLP is a huge plus)

Skills And Abilities

• Proficient in python, TensorFlow, keras and pytorch.
• Good experience in:
• SQL and non-relational databases.
• Data analytics reports generation.
• ML model development deployment.

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Main tasks and responsibilities (the position exists to perform the below functions and essential activities)

Build and optimize web applications from the front end to the back end.

Integrate user-facing elements using server-side logic and connecting the application with the cloud infrastructure.

Design and implement databases to store and retrieve data efficiently.

Optimize database performance and ensure data integrity.

Develop data pipelines for ETL (Extract, Transform, Load) processes.

Design, develop, and implement machine learning models to solve specific business problems using algorithms suitable for the task.

Identify and select relevant features or variables that contribute to the performance of machine learning models.

Analyse and understand large data sets to identify patterns, trends, and insights relevant to business goals.

Clean and prepare raw data for analysis, ensuring data quality and handling missing and inconsistent information.

Integrate and process data from various sources to support business needs.

Implement security measures for cloud-based solutions, including access controls, encryption, and compliance with industry standards. Monitor and optimize the performance of cloud-based applications and infrastructure.

Identify and address bottlenecks to ensure optimal system performance.

Collaborate with cross-functional teams, including other developers, data scientists, and system administrators.

Communicate technical concepts effectively to non-technical stakeholders.

Adhere to agile development methodologies and participate in sprint planning, reviews, and retrospectives.

Develop and maintain database architectures using MSSQL.

Collaborate with stakeholders to gather and comprehend business requirements for data collection and analysis.

Perform data validation to ensure accuracy, completeness, and consistency of data.

Analyse data sets, generate insights, and create reports using Power BI or similar tools.

Utilize Python for data manipulation, analysis, and automation tasks.

Integrate and work with various APIs for data extraction and manipulation.

Main tasks and responsibilities (the position exists to perform the below functions and essential activities)

Build and optimize web applications from the front end to the back end.

Integrate user-facing elements using server-side logic and connecting the application with the cloud infrastructure.

Design and implement databases to store and retrieve data efficiently.

Optimize database performance and ensure data integrity.

Develop data pipelines for ETL (Extract, Transform, Load) processes.

Design, develop, and implement machine learning models to solve specific business problems using algorithms suitable for the task.

Identify and select relevant features or variables that contribute to the performance of machine learning models.

Analyse and understand large data sets to identify patterns, trends, and insights relevant to business goals.

Clean and prepare raw data for analysis, ensuring data quality and handling missing and inconsistent information.

Integrate and process data from various sources to support business needs.

Implement security measures for cloud-based solutions, including access controls, encryption, and compliance with industry standards. Monitor and optimize the performance of cloud-based applications and infrastructure.

Identify and address bottlenecks to ensure optimal system performance.

Collaborate with cross-functional teams, including other developers, data scientists, and system administrators.

Communicate technical concepts effectively to non-technical stakeholders.

Adhere to agile development methodologies and participate in sprint planning, reviews, and retrospectives.

Develop and maintain database architectures using MSSQL.

Collaborate with stakeholders to gather and comprehend business requirements for data collection and analysis.

Perform data validation to ensure accuracy, completeness, and consistency of data.

Analyse data sets, generate insights, and create reports using Power BI or similar tools.

Utilize Python for data manipulation, analysis, and automation tasks.

Integrate and work with various APIs for data extraction and manipulation.

Oryx Universal College in partnership with Liverpool John Moores University | Full time

We are seeking a highly skilled and innovative Artificial Intelligence and Machine Learning Engineer to join our team. The ideal candidate will be responsible for designing, developing, and deploying AI and ML models that drive impactful solutions across various domains, including education, data analytics, automation, and smart systems. You will work alongside interdisciplinary teams to integrate cutting-edge technologies into practical applications, transforming data into intelligent action.

Key Responsibilities:

• Design, train, evaluate, and deploy machine learning and deep learning models
  
• Build and maintain scalable AI solutions for real-time or batch processing systems.
  
• Optimise model performance, including accuracy, latency, and resource consumption.
  
• Collaborate with data engineers and analysts to source, clean, and transform data.
  
• Apply advanced statistical and data mining techniques to extract meaningful patterns.
  
• Stay updated with the latest advancements in AI and ML technologies.
  
• Prototype innovative solutions, contribute to research publications, and recommend adoption of new frameworks.
  
• Systems Integration
  
• Develop APIs and services to integrate AI solutions into existing platforms or applications.
  
• Collaborate with software engineers and DevOps teams to ensure production-level stability.
  
• Work closely with academic and operational teams to understand business needs and translate them into technical solutions.
  
• Prepare documentation, reports, and presentation materials to communicate findings and methodologies.
  

Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or related field (Master’s or PhD preferred).

Minimum 3 years of hands-on experience in AI/ML engineering or data science roles.

Proficient in Python and common ML libraries (e.g., TensorFlow, PyTorch, scikit-learn, Keras).

Strong understanding of machine learning algorithms, neural networks, natural language processing (NLP), and computer vision.

Experience in model deployment using cloud platforms (e.g., AWS, Azure, GCP) or containerised environments (Docker, Kubernetes).

Knowledge of MLOps tools and CI/CD pipelines for ML projects.

Familiarity with big data platforms (e.g., Spark, Hadoop).

Experience with academic or educational systems (LMS, AI in education) is a plus.

Demonstrated contributions to open-source projects, research publications, or hackathons.