Senior Machine Learning Engineer

Responsibilities

• Design, build, and maintain scalable production-grade ML systems and pipelines using modern engineering practices including CI/CD, testing, monitoring, and observability.
• Translate ML science into reliable, scalable products that progress from experimentation to production delivery and operational use.
• Develop impactful ML products using statistical modeling, deep learning, and AI techniques across operational, scientific, and R&D domains.
• Convert complex scientific and business problems into well-scoped ML solutions delivering actionable insights and deployable capabilities.
• Architect and optimize ML systems for performance, scalability, and reliability in production environments.
• Collaborate with data scientists, data engineers, software engineers, and domain experts in cross-disciplinary teams.
• Adhere to and promote engineering and data science guidelines including design reviews, unit tests, monitoring, code reviews, and documentation.
• Present technical results, trade-offs, and product outcomes to peers and senior stakeholders.
• Contribute to improving developer velocity, engineering standards, and shared tooling.
• Mentor junior team members and contribute to the technical growth of the broader team.

Requirements

• MSc or PhD in a quantitative field (or equivalent experience in Computer Science, Mathematics, Physics, Engineering, or related discipline).
• Typically 5+ years hands-on experience designing, prototyping, productionizing, maintaining, and scaling ML and data science products in sophisticated environments.
• Strong expertise in machine learning algorithms, statistical modeling, and optimization with a track record of producing production-grade solutions.
• Applied knowledge across all stages of the data and model lifecycle using ML tools.
• Solid understanding of the mathematical foundations of statistics, machine learning, and scientific computing.
• Proficient in one or more object-oriented programming languages (Python, Go, Java, C++).
• Advanced SQL skills.
• Experience with modern ML engineering practices including MLOps, model lifecycle management, CI/CD, and monitoring.
• Familiarity with experimental design, analysis, and scientific methodology.
• Customer-focused and pragmatic with emphasis on value delivery and rigorous attention to detail.
• Strong stakeholder management and ability to influence across teams and organizations.
• Continuous learning mindset and drive for improvement.
• Experience with big data technologies such as Hadoop, Hive, Spark.
• Experience with generative AI, LLMs, or retrieval-augmented generation (RAG).
• Exposure to Agentic AI concepts including autonomous agents, tool use, and orchestration frameworks.
• Experience applying ML/AI to scientific or R&D workflows with emphasis on deployable ML products from research (e.g., simulation, optimization, physics-informed models).
• Familiarity with model interpretability, uncertainty quantification, and advanced experimental methodologies.
• Proven publications, invention disclosures, or patents in ML/AI.
• No prior energy industry experience required.

Technologies

• Python
• Go
• Java
• C++
• SQL
• Hadoop
• Hive
• Spark

Benefits

• Competitive compensation and benefits package.
• Opportunity to work on cutting-edge ML and AI problems at global scale.
• A culture that values scientific rigor, engineering excellence, and continuous learning.
• Hybrid working arrangements and a commitment to work-life balance.
• Career development pathways in a world-class technology organization.

Travel

Negligible travel should be expected with this role.

Relocation

This role is not eligible for relocation.

Remote

This position is a hybrid of office and remote working.