Senior Machine Learning Engineer

## Senior Machine Learning Engineer Apply remote type:
This position is a hybrid of office/remote working locations:
United Kingdom - Sunburytime type:
Full time posted on:
Posted Todaytime left to apply:
End Date:
July 31, 2026 (13 days left to apply) job requisition :
RQ113368
** Entity:
** Technology
* * Job Family Group:
** IT&S Group
*
* Job Description:

**##
** 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 know.##
** Role Summary
** We are looking for a Senior Machine Learning Engineer who combines deep machine learning expertise with strong software engineering subject area 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 field — 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 authorities — 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 demonstrating 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 authorities 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 partners.
* Actively supply to improving developer velocity, engineering standards, and shared tooling.
* Mentor junior team members and chip in to the technical growth of the wider team.##
** Qualifications
* *** Essential
* ** MSc, PhD degree or equivalent experience in a quantitative field (e.g. Computer Science, Mathematics, Physics, Engineering, or related discipline).
* Hands-on experience designing, prototyping, product ionizing, maintaining, and scaling ML/data science products in complex 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 partner management and ability to influence across teams and organisations.
* Continuous learning and improvement mentality.##
** 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,…