Baker Hughes

Lead AI Engineer

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3 Locations

In-Office

Energy

The Role

Lead AI Engineer

Are you a highly motivated, creative individual and passionate about sales and proposals?

Would you like to be a part of successful team?

Join our Artificial Intelligence Engineering Team

We design, build, and operate AI services that power critical business processes, including real-time decisioning, document understanding, predictive maintenance, computer vision, and Generative AI use cases. Our focus is on turning validated AI models into reliable, secure, and scalable production services.

Partner with the best

You will play a key role in enabling Baker Hughes’ mission to make energy safer, cleaner, and more efficient through intelligent technologies. As a Lead AI Engineer, you will lead the design and delivery of AI serving capabilities that meet strict requirements for performance, reliability, cost control, and operational readiness, while mentoring other engineers and driving consistent engineering standards across teams.

As a Lead AI Engineer, you will also be responsible for:

Leading the design, analysis, implementation, and integration of AI model serving solutions.
Designing and standardizing serving architectures for AI and GenAI use cases.
Defining and implementing safe rollout and rollback strategies. Driving performance, scalability, and cost optimization.
Establishing and reviewing runtime resilience patterns. Providing technical leadership and coaching through design and code reviews.
Developing and reviewing performance, load, resiliency, and cost test plans.
Ensuring operational readiness for production launches. Participating in architecture, operational readiness, and security reviews.
Collaborating with Platform, MLOps, Reliability, Security, Data, and Product teams.

Fuel your passion!

To be successful in this role you will:

A Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field.
Strong experience delivering production-grade software systems.
Expertise in Python development.
Experience with containerized, microservice-based architectures.
Strong understanding of API design and versioning. Experience with AWS.
Knowledge of CI/CD pipelines and DevOps practices.
Experience mentoring engineers and leading technical initiatives.

Work in a way that works for you

We recognize that everyone is different and that the way in which people want to work and deliver at their best is different for everyone too.

Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive.

Working with us

Our people are at the heart of what we do at Baker Hughes. We know we are better when all of our people are developed, engaged and able to bring their whole authentic selves to work. We invest in the health and well-being of our workforce, train and reward talent and develop leaders at all levels to bring out the best in each other.

Working for you

Our inventions have revolutionized energy for over a century. But to keep going forward tomorrow, we know we have to push the boundaries today. We prioritize rewarding those who embrace change with a package that reflects how much we value their input. Join us, and you can expect.

Contemporary work-life balance policies and wellbeing activities

Comprehensive private medical care options

Safety net of life insurance and disability programs

Tailored financial programs

Additional elected or voluntary benefits

The Baker Hughes internal title for this role is: Lead Engineer, Mathematics & Data Science, Disciplinary Engineering and Science

Baker Hughes Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Baker Hughes and has not been reviewed or approved by Baker Hughes.

Retirement Support — Feedback suggests retirement contributions combine automatic employer funding with a dollar‑for‑dollar match, with immediate vesting on the match. This structure can meaningfully increase savings for employees who participate consistently.
Equity Value & Accessibility — Feedback suggests a discounted employee stock purchase program with regular purchase periods and no brokerage fees provides accessible ownership upside. Program parameters are clearly laid out through the benefits hub and plan materials.
Leave & Time Off Breadth — Feedback suggests exempt staff have flexible, manager‑approved time off while non‑exempt employees accrue vacation and receive paid personal time. Company‑paid holidays and paid parental leave further broaden time‑away options.