Senior Machine Learning Engineer in Greater London

Energy Jobline ZR; Greater London; Hybrid; GBP 65,000 - 90,000; Full time

Job summary

A leading consultancy in AI based in London is seeking a Senior LLM Engineer to design and deploy LLM systems in real-world environments. You will work closely with internal teams and clients, requiring strong Python and model deployment experience. With a focus on cost-efficiency, this role is perfect for someone with 3+ years in ML/AI and the ability to work in a hybrid setup.

Benefits

Modern kit (MacBook etc.)

27 days annual leave + bank holidays

4-week paid sabbatical after 4 years tenure

Regular team meet-ups and workshops

Sensible working hours

Clear progression opportunities

Qualifications

• 3+ years experience in ML/AI roles, ideally from a data science or applied ML background.
• Able to measure output quality and reduce hallucination risks.
• Familiar with optimizing inference performance.

Responsibilities

• Own the design and build of LLM-based systems end-to-end.
• Fine-tune and adapt models rather than just prompt-engineering.
• Deploy models into production environments where constraints exist.

Skills

Hands-on LLM experience beyond prototyping/notebooks

Strong Python skills

Experience with PyTorch/Hugging Face

Experience deploying models into production

Familiarity with vector stores and RAG patterns

Comfortable operating in a hybrid environment

MLFlow/MLOps experience

Job description

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We focus on the Oil & Gas, Renewables, Engineering, Power, and Nuclear markets as well as emerging technologies in EV, Battery, and Fusion. We are committed to ensuring that we offer the most exciting career opportunities from around the world for our jobseekers.

Job Description

Senior LLM Engineer London | Hybrid (2 days per week on-site, Bank area)

My client is a long-established consultancy that originally built its reputation in data engineering and wider data transformation, and over the past few years has grown a strong applied AI practice. They tend to work with UK organisations where data security, reliability and explainability actually matter, so think regulated, risk-aware, or operationally critical environments rather than hype-driven MVPs.

The current AI/ML group is around eight senior engineers, with backing to grow sensibly (not a hiring spree). This role sits within that team and is focused on designing and deploying LLM systems that make it into production, are cost-efficient, and work reliably in the real world.

What youll be doing:

• Owning the design and build of LLM-based systems end-to-end
• Fine-tuning and adapting models (LoRA, instruction tuning, PEFT etc) rather than just prompt-engineering
• Building RAG workflows, embedding strategies, memory layers and domain grounding
• Working out how to measure output quality, reduce hallucination risk and improve robustness
• Optimising inference performance (quantisation, distillation, pruning, batching, caching)
• Deploying models into production environments where latency, cost and privacy are real constraints
• Working closely with both internal engineers and client teams to ensure what gets built actually lands well

What theyre looking for:

• Hands-on LLM experience beyond prototyping / notebooks
• Strong Python and experience with PyTorch / Hugging Face / similar tooling
• Experience deploying models into production (not just training them)
• Familiarity with vector stores and RAG patterns
• Comfortable operating in a hybrid environment and speaking with stakeholders where required
• Someone who enjoys solving real problems end-to-end: from understanding the domain designing the approach shipping the implementation
• Experience of MLFlow / MLOps highly desirable

Important notes (just to be upfront):

• They cannot sponsor visas, so youll need existing right to work in the UK
• No relocation support youll need to already be UK-based and able to be in London (Bank area) twice a week
• This is a senior role typically someone with 3+ years experience in ML/AI roles, ideally from a data science or applied ML background

Benefits / set-up:

• Modern kit (MacBook etc.)
• 27 days annual leave + bank holidays
• 4-week paid sabbatical after 4 years tenure
• Regular team meet-ups, workshops, and knowledge-sharing sessions
• Sensible working hours grown-up environment, not crunch culture
• Clear progression as the AI group continues to scale
• Stable team, low-ego culture, and work that isnt just slideware or demos

If you are interested in applying for this job please press the Apply Button and follow the application process. Energy Jobline wishes you the very best of luck in your next career move.