Senior Machine Learning Engineer

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About us
Our purpose is to bring together people, energy and markets to power and navigate a changing world. In a time of constant change and possibility we need new talent to pursue commercial opportunities, fueled by world-class insight and expertise. We’re always striving for more innovative digital solutions, sustainable outcomes and closer collaboration across our company and beyond, and you could be part of that too.

Together we continue to grow as the world’s leading energy company!

Role Summary

We are looking for a Senior Machine Learning Engineer who combines deep machine learning expertise with strong software engineering discipline to design, build, and deploy production-grade ML and AI systems.

This role goes beyond traditional ML engineering. You will apply machine learning science as a core discipline — developing novel algorithms and models that are not only experimentally validated but architected and deployed as scalable, reliable products. Whether it's advancing NLP, optimisation, simulation, or generative AI, you will deliver solutions that transition seamlessly from research to production and create measurable value.

You will work as part of a cross-disciplinary team alongside data scientists, software engineers, data engineers, and domain experts — translating complex scientific and business problems into deployable ML products.

Key Responsibilities

• Design, build, and maintain scalable, production-grade machine learning systems and pipelines using modern engineering practices (CI/CD, testing, monitoring, observability).
• Apply machine learning science to develop novel algorithms and models that are deployed as reliable, scalable products — not limited to experimentation but extending through to production delivery and operational use.
• Build impactful ML products leveraging statistical modelling, deep learning, and AI techniques across operational, scientific, and R&D domains.
• Translate complex scientific and business problems into well-scoped ML solutions, delivering actionable insights and deployable capabilities.
• Architect and optimise ML systems for performance, scalability, and reliability in production environments.
• Collaborate closely with data scientists, data engineers, software engineers, and domain experts as part of cross-disciplinary teams.
• Adhere to and advocate for engineering and data science guidelines (technical design, design reviews, unit testing, monitoring & alerting, code reviews, documentation).
• Present technical results, trade-offs, and product outcomes to peers and senior interested parties.
• Actively contribute to improving developer velocity, engineering standards, and shared tooling.
• Mentor junior team members and contribute to the technical growth of the wider team.

Qualifications

Essential

• MSc or PhD degree or equivalent experience in a quantitative field (e.g. Computer Science, Mathematics, Physics, Engineering, or related discipline).
• Hands-on experience (typically 5+ years) designing, prototyping, product ionizing, maintaining, and scaling ML/data science products in sophisticated environments.
• Strong and demonstrable expertise in machine learning algorithms, statistical modelling, and optimisation techniques — with a track record of applying these to build production-grade solutions.
• Applied knowledge of data science and ML tools across all stages of the data and model lifecycle.
• Thorough understanding of the mathematical foundations of statistics, machine learning, and scientific computing.
• Strong programming experience in one or more object-oriented languages (e.g. Python, Go, Java, C++).
• Advanced SQL knowledge.
• Experience with modern ML engineering practices including MLOps, model lifecycle management, CI/CD, and monitoring.
• Knowledge of experimental design, analysis, and scientific methodology.
• Customer-centric and pragmatic mentality with a focus on value delivery and swift execution, while maintaining rigour and attention to detail.
• Strong stakeholder management and ability to influence across teams and organisations.
• Continuous learning and improvement mindset.

Desired

• Experience with big data…