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Join the Team!
Join our Process & Pipeline Services Software & Data Science team to lead the development and deployment of scalable, production-grade data science applications. You will bridge the gap between data science innovation and software engineering excellence, delivering intelligent systems that power the automated analysis of pipeline inspection data.
Partner with the best
Reporting to the Senior Engineering Manager – Software and Data Science, the Lead Data Science Engineer will play a key role in transforming advanced analytics and machine learning models into robust, secure, and high-performance software products.
As a Lead Data Science Engineer, you will be responsible for:
Data Science & Machine Learning
- Designing, developing, and validating machine learning models for anomaly detection, signal processing, and classification.
- Collaborating with domain experts to translate data into actionable insights using statistical and ML techniques.
- Continuously evaluating model performance and retrain pipelines to ensure accuracy and reliability in production.
Productization & Engineering
- Leading the end-to-end productization of data science solutions, from prototype to scalable deployment.
- Building and maintaining robust data pipelines and APIs that integrate seamlessly with enterprise software systems.
- Applying software engineering best practices (CI/CD, version control, testing) to data science workflows.
Collaboration & Leadership
- Working closely with software engineers, product managers, and SMEs to align data science initiatives with product goals.
- Providing technical mentorship to junior data scientists and engineers.
- Contributing to architectural decisions and technology evaluations for AI/ML infrastructure.
Fuel your passion
To be successful in this role you will:
- Have 5+ years of experience in data science, machine learning, or applied AI.
- Possess proven experience deploying ML models into production environments at scale.
- Possess strong programming skills in Python and C++ Java, with experience in software engineering practices.
- Be proficient in ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and data pipeline tools.
- Have a multi-year track record in managing large datasets / with data-driven systems.
- Have familiarity with containerization and orchestration (e.g., Docker, Kubernetes).
- Possess hands-on experience with MLOps practices and tools for managing the ML lifecycle.
- Demonstrate excellent communication and collaboration skills in cross-functional team
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. In this role, we can offer the following flexible working patterns:
- 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
- Education Assistance
- Generous Parental Leave
- Mental Health Resources
- Dependent Care
- Additional elected or voluntary benefits
