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Join to apply for the Engineering Manager - MLOps & Analytics role at Canonical

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Join to apply for the Engineering Manager - MLOps & Analytics role at Canonical

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The role of an Engineering Manager at Canonical

As an Engineering Manager at Canonical, you must be technically strong, but your main responsibility is to run an effective team and develop the colleagues you manage. You will develop and review code as a leader, while at the same time staying aware of that the best way to improve the product is to ensure that the whole team is focused, productive and unblocked.

You are expected to help them grow as engineers, do meaningful work, do it outstandingly well, find professional and personal satisfaction, and work well with colleagues and the community. You will also be expected to be a positive influence on culture, facilitate technical delivery, and regularly reflect with your team on strategy and execution.

You will collaborate closely with other Engineering Managers, product managers, and architects, producing an engineering roadmap with ambitious and achievable goals.

We expect Engineering Managers to be fluent in the programming language, architecture, and components that their team uses, in this case popular open-source machine learning tools like Kubeflow, MLFlow, and Feast.

Code reviews and architectural leadership are part of the job. The commitment to healthy engineering practices, documentation, quality and performance optimisation is as important, as is the requirement for fair and clear management, and the obligation to ensure a high-performing team.

Location: This is a Globally remote role.

What your day will look like

• Manage a distributed team of engineers and its MLOps/Analytics portfolio
• Organize and lead the team's processes in order to help it achieve its objectives
• Conduct one-on-one meetings with team members
• Identify and measure team health indicators
• Interact with a vibrant community
• Review code produced by other engineers
• Attend conferences to represent Canonical and its MLOps solutions
• Mentor and grow your direct reports, helping them achieve their professional goals
• Work from home with global travel for 2 to 4 weeks per year for internal and external events
  
  

What we are looking for in you

• A proven track record of professional experience of software delivery
• Professional python development experience, preferably with a track record in open source
• A proven understanding of the machine learning space, its challenges and opportunities to improve
• Experience designing and implementing MLOps solutions
• An exceptional academic track record from both high school and preferably university
• Willingness to travel up to 4 times a year for internal events
  
  

Additional skills that you might also bring

The following skills may be helpful to you in the role, but we don't expect everyone to bring all of them.

• Hands-on experience with machine learning libraries, or tools.
• Proven track record of building highly automated machine learning solutions for the cloud.
• Experience with building machine learning models
• Experience with container technologies (Docker, LXD, Kubernetes, etc.)
• Experience with public clouds (AWS, Azure, Google Cloud)
• Experience in the Linux and open-source software world
• Working knowledge of cloud computing
• Passionate about software quality and testing
• Experience working on a distributed team on an open source project -- even if that is community open source contributions.
• Demonstrated track record of Open Source contributions
  
  

What we offer you

We consider geographical location, experience, and performance in shaping compensation worldwide. We revisit compensation annually (and more often for graduates and associates) to ensure we recognise outstanding performance. In addition to base pay, we offer a performance-driven annual bonus. We provide all team members with additional benefits, which reflect our values and ideals. We balance our programs to meet local needs and ensure fairness globally.

• Distributed work environment with twice-yearly team sprints in person - we've been working remotely since 2004!
• Personal learning and development budget of USD 2,000 per year
• Annual compensation review
• Recognition rewards
• Annual holiday leave
• Maternity and paternity leave
• Employee Assistance Programme
• Opportunity to travel to new locations to meet colleagues from your team and others
• Priority Pass for travel and travel upgrades for long haul company events
  
  

About Canonical

Canonical is a pioneering tech firm that is at the forefront of the global move to open source. As the company that publishes Ubuntu, one of the most important open source projects and the platform for AI, IoT and the cloud, we are changing the world on a daily basis. We recruit on a global basis and set a very high standard for people joining the company. We expect excellence - in order to succeed, we need to be the best at what we do.

Canonical has been a remote-first company since its inception in 2004. Work at Canonical is a step into the future, and will challenge you to think differently, work smarter, learn new skills, and raise your game. Canonical provides a unique window into the world of 21st-century digital business.

Canonical is an equal opportunity employer

We are proud to foster a workplace free from discrimination. Diversity of experience, perspectives, and background create a better work environment and better products. Whatever your identity, we will give your application fair consideration.

Seniority level

• Seniority level Mid-Senior level

Employment type

• Employment type Full-time

Job function

• Job function Engineering and Information Technology
• Industries Software Development

Referrals increase your chances of interviewing at Canonical by 2x

Sign in to set job alerts for “Engineering Manager” roles. Engineering Manager - Solutions Engineering Software Engineering Manager - Sustaining Engineering Technical Manager - Automotive and Industrial Engineering Manager - Public Cloud, Python, Golang Engineering Manager - Build and Release Infrastructure Software Engineering Manager - Desktop and Embedded Linux Optimisation Engineering Manager - Build and Release Infrastructure Software Engineering Manager - Container and Virtualisation Infrastructure Software Engineering Manager, Ubuntu Gaming Salesforce Engineering Manager, Commercial Systems Software Platform Engineering Manager - Ubuntu for Next-Gen Silicon Engineering Manager - Security Standards and Hardening Linux Engineering Manager - Optimisation for Latest Hardware Embedded Linux Field Engineering Manager Linux Enablement - Software Engineering Manager Ubuntu Enablement - Software Engineering Manager Revenue Accounting Manager - Software Industry, IFRS 15, NetSuite

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Join to apply for the

Engineering Manager - MLOps & Analytics

role at

Canonical 3 days ago Be among the first 25 applicants Join to apply for the

Engineering Manager - MLOps & Analytics

role at

Canonical Get AI-powered advice on this job and more exclusive features. The role of an Engineering Manager at Canonical

As an Engineering Manager at Canonical, you must be technically strong, but your main responsibility is to run an effective team and develop the colleagues you manage. You will develop and review code as a leader, while at the same time staying aware of that the best way to improve the product is to ensure that the whole team is focused, productive and unblocked.

You are expected to help them grow as engineers, do meaningful work, do it outstandingly well, find professional and personal satisfaction, and work well with colleagues and the community. You will also be expected to be a positive influence on culture, facilitate technical delivery, and regularly reflect with your team on strategy and execution.

You will collaborate closely with other Engineering Managers, product managers, and architects, producing an engineering roadmap with ambitious and achievable goals.

We expect Engineering Managers to be fluent in the programming language, architecture, and components that their team uses, in this case popular open-source machine learning tools like Kubeflow, MLFlow, and Feast.

Code reviews and architectural leadership are part of the job. The commitment to healthy engineering practices, documentation, quality and performance optimisation is as important, as is the requirement for fair and clear management, and the obligation to ensure a high-performing team.

Location:

This is a Globally remote role.

What your day will look like

Manage a distributed team of engineers and its MLOps/Analytics portfolio Organize and lead the team's processes in order to help it achieve its objectives Conduct one-on-one meetings with team members Identify and measure team health indicators Interact with a vibrant community Review code produced by other engineers Attend conferences to represent Canonical and its MLOps solutions Mentor and grow your direct reports, helping them achieve their professional goals Work from home with global travel for 2 to 4 weeks per year for internal and external events

What we are looking for in you

A proven track record of professional experience of software delivery Professional python development experience, preferably with a track record in open source A proven understanding of the machine learning space, its challenges and opportunities to improve Experience designing and implementing MLOps solutions An exceptional academic track record from both high school and preferably university Willingness to travel up to 4 times a year for internal events

Additional skills that you might also bring

The following skills may be helpful to you in the role, but we don't expect everyone to bring all of them.

Hands-on experience with machine learning libraries, or tools. Proven track record of building highly automated machine learning solutions for the cloud. Experience with building machine learning models Experience with container technologies (Docker, LXD, Kubernetes, etc.) Experience with public clouds (AWS, Azure, Google Cloud) Experience in the Linux and open-source software world Working knowledge of cloud computing Passionate about software quality and testing Experience working on a distributed team on an open source project -- even if that is community open source contributions. Demonstrated track record of Open Source contributions

What we offer you

We consider geographical location, experience, and performance in shaping compensation worldwide. We revisit compensation annually (and more often for graduates and associates) to ensure we recognise outstanding performance. In addition to base pay, we offer a performance-driven annual bonus. We provide all team members with additional benefits, which reflect our values and ideals. We balance our programs to meet local needs and ensure fairness globally.

Distributed work environment with twice-yearly team sprints in person - we've been working remotely since 2004! Personal learning and development budget of USD 2,000 per year Annual compensation review Recognition rewards Annual holiday leave Maternity and paternity leave Employee Assistance Programme Opportunity to travel to new locations to meet colleagues from your team and others Priority Pass for travel and travel upgrades for long haul company events

About Canonical

Canonical is a pioneering tech firm that is at the forefront of the global move to open source. As the company that publishes Ubuntu, one of the most important open source projects and the platform for AI, IoT and the cloud, we are changing the world on a daily basis. We recruit on a global basis and set a very high standard for people joining the company. We expect excellence - in order to succeed, we need to be the best at what we do.

Canonical has been a remote-first company since its inception in 2004. Work at Canonical is a step into the future, and will challenge you to think differently, work smarter, learn new skills, and raise your game. Canonical provides a unique window into the world of 21st-century digital business.

Canonical is an equal opportunity employer

We are proud to foster a workplace free from discrimination. Diversity of experience, perspectives, and background create a better work environment and better products. Whatever your identity, we will give your application fair consideration.

Seniority level

Seniority level Mid-Senior level Employment type

Employment type Full-time Job function

Job function Engineering and Information Technology Industries Software Development Referrals increase your chances of interviewing at Canonical by 2x Sign in to set job alerts for “Engineering Manager” roles.

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Revenue Accounting Manager - Software Industry, IFRS 15, NetSuite

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Technology Consulting
- Microsoft Data Analytics
- MENA

With a broad understanding of the full lifecycle of our clients' business, EY has the knowledge and experience to integrate cloud strategy where it makes the most impact and transformation. EY's Microsoft cloud solutions offer a balance of business, technology, and strategy. EY works with high profile clients across the region, working to solve some of their most challenging issues. As our practice continues to grow quickly, EY is actively investing in the latest cloud technology and talent. This is the perfect time to join and make your mark on significant cloud projects across a wide variety of industries, platforms, and technologies.

**The opportunity**

EY is investing significantly in their award-winning Microsoft Data and AI practice. You will help our clients to enable better business outcomes while working in the rapidly growing cloud space. You will have the opportunity to lead and develop your skill set to keep up with the ever-growing demands of the modern data platform. During implementation you will solve complex analytical problems in an effort to bring data to insights and enable the use of ML and AI at scale for your clients. This is a high growth area and a high visibility role with plenty of opportunities to enhance your skillset and build your career.

**Your key responsibilities**
- Designing, Architecting, and Developing solutions leveraging cloud big data technology to ingest, process and analyze large, disparate data sets to exceed business requirements.
- Unifying, enriching, and analyzing customer data to derive insights and opportunities.
- Leveraging in-house data platforms as needed and recommending and building new data platforms/solutions as required to exceed business requirements.
- Clearly communicating findings, recommendations, and opportunities to improve data systems and solutions.
- Demonstrating deep understanding of big data technology, concepts, tools, features, functions, and benefits of different approaches
- Seeking out information to learn about emerging methodologies and technologies.
- Clarifying problems by driving to understand the true issue.
- Looking for opportunities for improving methods and outcomes
- Collaborating, influencing, and building consensus through constructive relationships and effective listening
- Solving problems by incorporating data into decision making

**To qualify for the role, you must have**
- Bachelor's degree, or MS degree in Business, Economics, Technology Entrepreneurship, Computer Science, Informatics, Statistics, Applied Mathematics, Data Science, or Machine Learning
- Minimum of 8+ years of professional consulting experience in business or technology consulting or similar roles
- Strong SQL skills
- Deep experience with at least one cloud platform; Azure, Amazon, or Google.
- Experience with the toolset of Azure Synapse Analytics using Data Flows, building Spark notebooks, and building queries.
- Experience navigating various types of database models to build data sets for analytics and model training and development.
- Experience modelling data in Power BI and other PowerApps
- Experience working with different data sources in Azure that connect to Microsoft Azure Platform
- Outstanding analytical, conceptual, and problem-solving skills
- Communication and critical thinking is essential, must be able to listen and understand the question and develop and deliver clear insights
- Independent and able to manage and prioritize workload.
- Ability to adapt quickly and positively to change.

**Other Skills and attributes for success**
- Leading team members in the development of applicable methodologies, tools, approaches, points of view, thought leadership and accelerators to differentiate EY in the Cloud Technology market.
- Being proactive and driven to continually learn emerging technologies and business best practices.
- Developing long-term relationships and networks both internally and externally.
- Interacting and communicating effectively with teammates, clients, stakeholders, and executives.
- Being visible in the market to promote new ideas in your domain and the excellence in cloud consulting services offered by EY.

**What working at EY offers**

We offer a competitive compensation package where you'll be rewarded based on your performance and recognized for the value you bring to our business. In addition, our Total Rewards package includes regional competitive package.

Plus, we offer:

- The opportunity to manage a portfolio of talent within a designated service line
- A collaborative environment where everyone works together to create a better working world
- Excellent training and development prospects, both through established programs and on-the-job training
- An excellent team of senior colleagues dedicated to managing and varying your workload

**About EY**

As a global leader in assurance, tax, transaction and advisory services, we hire and develop t

JOB TO BE BASED IN SAUDI ARABIA

Overview:

We are seeking Downstream Data Analytics Engineer (Data Scientist) to join our Digital Engineering Solutions Division under Process & Control Systems Department.

Process and Control Systems Department provides services in the field of process engineering, automation, new energy and digitalization to various entities within Aramco.

As a Data Analytics Engineer your role will be to lead innovation within the business and define how the business creates additional value through the utilization of its data assets and analytics. You will identify and solve strategic and tactical analytic business problems to enhance operational efficiency.

Key Responsibilities:

As a successful candidate you will be required to perform the following:

• Identify and develop advanced analytics use cases to resolve complex technical challenges, optimize processes, enhance revenue, ensure environmental sustainability, and improve safety.
• Drive ideas from conception to production using best-in-class Machine Learning Operations (MLOps) and Development Operations (DevOps) practices.
• Develop and optimize Machine Learning (ML) models and pipelines, ensuring their efficient deployment, monitoring, and scaling.
• Explore diverse data sources to improve predictive modeling and optimize business strategies.
• Assess Artificial Intelligence (AI) tools and methods for data analysis, enhancing business impact and decision-making.
• Implement predictive modeling techniques to optimize production facilities, revenue streams, and operational efficiencies.
• Generate documentation in line with established standards to support the development and deployment process.
• Collaborate with cross-functional teams, including IT, engineering, and business stakeholders, to drive data-driven solutions.
• Contribute to technical task forces investigating incidents and solving domain-specific problems using AI/ML techniques.
• Publish research papers for peer-reviewed journals and presents findings to other organizations and conferences to advance industry knowledge.
• Promotes a learning environment through knowledge-sharing, and fosters a culture of continuous learning and innovation.
• Provide leadership and mentorship to junior team members and specialists.

Minimum Requirements:

As a successful candidate you will hold a:

• Bachelor’s degree in Data Science, Computer Science, Engineering, or a related field. An advanced degree (Master’s or PhD) focused on Data Science, AI, or ML Engineering with a background in Engineering is highly preferred.
• 18 years of overall experience, with hands-on experience in Data Science, Natural Language Processing (NLP), Computer Vision, and/or ML projects in UPSTREAM and/or DOWNSTREAM OIL & GAS INDUSTRY.
• Expertise in MLOps, DevOps, AIOps, DataOps and related operational frameworks for model deployment, monitoring, and automation.
• Experience in data collection, cleaning, preprocessing, and wrangling for industry-related problems based on domain knowledge.
• Proficiency in Platforms such as Python, R, SQL, SAS, Scala, and cloud platforms such as Azure and Google Cloud (Vertex AI).
• Expertise in visualization tools and packages; User Interface (UI) experience with Power Business Intelligence (Power BI) or similar tools.
• Experience with IT architecture and deploying models in on-prem environments.
• Strong understanding of continuous integration / continuous deployment (CI/CD) pipelines, containerization (Docker, Kubernetes), and automation frameworks.
• Demonstrated ability to publish research or contribute to industry knowledge through journal papers, conference proceedings, or whitepapers preferred

REGRET ONLY SHORTLISTED CANDIDATES WILL BE CONTACTED

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JOB TO BE BASED IN SAUDI ARABIA Overview: We are seeking Downstream Data Analytics Engineer (Data Scientist) to join our Digital Engineering Solutions Division under Process & Control Systems Department. Process and Control Systems Department provides services in the field of process engineering, automation, new energy and digitalization to various entities within Aramco. As a

Data Analytics Engineer your role will be to lead innovation within the business and define how the business creates additional value through the utilization of its data assets and analytics. You will identify and solve strategic and tactical analytic business problems to enhance operational efficiency. Key Responsibilities: As a successful candidate you will be required to perform the following: Identify and develop advanced analytics use cases to resolve complex technical challenges, optimize processes, enhance revenue, ensure environmental sustainability, and improve safety. Drive ideas from conception to production using best-in-class Machine Learning Operations (MLOps) and Development Operations (DevOps) practices. Develop and optimize Machine Learning (ML) models and pipelines, ensuring their efficient deployment, monitoring, and scaling. Explore diverse data sources to improve predictive modeling and optimize business strategies. Assess Artificial Intelligence (AI) tools and methods for data analysis, enhancing business impact and decision-making. Implement predictive modeling techniques to optimize production facilities, revenue streams, and operational efficiencies. Generate documentation in line with established standards to support the development and deployment process. Collaborate with cross-functional teams, including IT, engineering, and business stakeholders, to drive data-driven solutions. Contribute to technical task forces investigating incidents and solving domain-specific problems using AI/ML techniques. Publish research papers for peer-reviewed journals and presents findings to other organizations and conferences to advance industry knowledge. Promotes a learning environment through knowledge-sharing, and fosters a culture of continuous learning and innovation. Provide leadership and mentorship to junior team members and specialists. Minimum Requirements: As a successful candidate you will hold a: Bachelor’s degree in Data Science, Computer Science, Engineering, or a related field. An advanced degree (Master’s or PhD) focused on Data Science, AI, or ML Engineering with a background in Engineering is highly preferred. 18 years of overall experience, with hands-on experience in Data Science, Natural Language Processing (NLP), Computer Vision, and/or ML projects in UPSTREAM and/or DOWNSTREAM OIL & GAS INDUSTRY. Expertise in MLOps, DevOps, AIOps, DataOps and related operational frameworks for model deployment, monitoring, and automation. Experience in data collection, cleaning, preprocessing, and wrangling for industry-related problems based on domain knowledge. Proficiency in Platforms such as Python, R, SQL, SAS, Scala, and cloud platforms such as Azure and Google Cloud (Vertex AI). Expertise in visualization tools and packages; User Interface (UI) experience with Power Business Intelligence (Power BI) or similar tools. Experience with IT architecture and deploying models in on-prem environments. Strong understanding of continuous integration / continuous deployment (CI/CD) pipelines, containerization (Docker, Kubernetes), and automation frameworks. Demonstrated ability to publish research or contribute to industry knowledge through journal papers, conference proceedings, or whitepapers preferred REGRET ONLY SHORTLISTED CANDIDATES WILL BE CONTACTED

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