We are looking for a Senior Machine Learning Engineer who combines deep machine learning expertise with strong software engineering field 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 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.
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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 best practices (technical design, design reviews, unit testing, monitoring & alerting, code reviews, documentation).
Present technical results, trade-offs, and product outcomes to peers and senior customers.
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 in a quantitative field (e.g. Computer Science, Mathematics, Physics, Engineering, or related discipline).
Hands-on experience (typically 5+ years) designing, prototyping, productionising, 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 mindset 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 sophisticated 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
[Complete by TA / HR with local benefits and compensation details]
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 know
Why join bp
Our purpose is to deliver energy to the world, today and tomorrow. For over 100 years, bp has focused on discovering, developing, and producing oil and gas in the nations where we operate. We are one of the few companies globally that can provide governments and customers with an integrated energy offering. Delivering our strategy sustainably is fundamental to achieving our ambition to be a net zero company by 2050 or sooner! At bp, we support our people to learn and grow in a diverse and ambitious environment. We believe that our team is strengthened by diversity. We are committed to fostering an inclusive environment in which everyone is respected and treated fairly.
Disclaimer
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform crucial job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
Even though the job is advertised as full time, please contact the hiring manager or the recruiter as flexible working arrangements may be considered.
We believe that our team is strengthened by diversity. We are committed to crafting 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, collaboration spaces in a modern office environment, and many others benefits.
What you can expect from us!
Our commitment to diversity, equity and inclusion:
At bp, you could be part of Business Resource Groups (BRGs) which believe in the power of inclusion, deeper connections, and shared experiences. They provide a place for employees to learn and share knowledge, to connect, and to improve. The BRGs focus on and encourage talent engagement, development, and retention while creating a broadened sense of community and inclusion for bp employees. The groups cultivate leadership growth by involving employees in developmental opportunities they would not otherwise have access to. Formal and informal mentoring also helps employees develop their professional goals and c
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