Senior Machine Learning Engineer

Job Description:

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, productionizing, 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 technologies (e.g. 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 machine learning and AI to scientific or R&D workflows - with emphasis on building deployable ML products from scientific research (e.g. simulation, optimisation, physics-informed models).
• Familiarity with model interpretability, uncertainty quantification, and advanced experimental methodologies.
• Proven record of publications, invention disclosures (IDFs), or patents in machine learning or AI.
• No prior experience in the energy industry required.

What We Offer

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

Equal Opportunity Employer

bp is an equal opportunity employer. We believe that diversity and inclusion drive innovation and are essential to our success. We welcome applications from all qualified individuals regardless of race, colour, religion, gender, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected characteristic.

We are committed to making reasonable adjustments for candidates with disabilities or long-term conditions. If you require any adjustments during the recruitment process, please let us kn

Why join bp:
At bp, we support our people to learn and grow in a diverse and challenging environment. We believe that our team is strengthened by diversity. We are committed to encouraging an inclusive environment in which everyone is respected and treated fairly.
There are many aspects of our employees' lives that are meaningful, so we offer benefits to enable your work to fit with your life. These benefits can include flexible working options, a generous paid parental leave policy, and excellent retirement benefits, among others!

Travel Requirement
Negligible travel should be expected with this role

Relocation Assistance:
This role is not eligible for relocation

Remote Type:
This position is a hybrid of office/remote working

Skills:
Cloud Platforms, Cloud Platforms, Collaboration, Communication, Configuration management and release, Continuous deployment and release, Creating a high performing team, Database Design, Digital Project Management, Documentation and knowledge sharing, Emerging technology monitoring, Facilitation, Information Security, Mentoring, Metrics definition and instrumentation, NoSql data modelling, Problem Solving, Relational Data Modelling, Risk Management, Scripting, Secure development, Service operations and resiliency, Software Design and Development, Solution Architecture, Source control and code management {+ 5 more}

Legal Disclaimer:

We are an equal opportunity employer. We do not discriminate on the basis of protected characteristics like race, religion, color, sex, national origin, sexual orientation, veteran status or disability status. Individuals with an accessibility need may request an adjustment/accommodation related to bp's recruiting process (e.g., accessing the job application, completing required assessments, participating in telephone screenings or interviews, etc.). If you would like to request an adjustment/accommodation related to the recruitment process, please contact us.

If you are selected for a position and depending upon your role, your employment may be contingent upon adherence to local policy. This may include pre-placement drug screening, medical review of physical fitness for the role, and background checks.