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Job Description

Senior AI Engineer

£90,000-£130,000

UK remote with London office with expectation to be seen in person at least once a fortnight ideally. If LDN based 2 days a week on site with wider team.

Equity options

25 days holiday + bank

Pension matched to 7%

Work abroad for up to 3 months

Are you looking to be part of a world-class data lead organisation who are continuously moving forward with the latest AI trends?

This company is a true innovator in building data driven products using machine learning, computer vision, natural processing, speech and audio, and knowledge/data mining. This person will be a senior engineer who will help both define and build the companies. In the role you will be building large scale machine learning systems, apply the latest techniques whilst working with an elite team of researchers and engineers.

No day will be the same, you will get to work on

Driving end to model development lifecycle, leading the team in best practices, ensuring reproducible research and well managed model delivery/deployment.

Collaborate cross functionally to share diverse ideas, understand business problems, and elevate/mentor your teammates.

Translate complex problems into well-defined scoped bets in an internal start-up style environment, dynamic and fast-paced.

Learn and apply ground-breaking research and approaches in advanced topics, iterating improvements with fail fast mentality.

Be a proactive sharer of compelling ideas/work to the rest of the team and organisation.

What do you need?

Not necessarily the title, we know in the world of AI Engineering you may come from a background of data science, engineering, machine learning although what is key is that you will be deeply involved with productionising and deploying.

Strong Python, SQL and programming skills

Hands on experience working within areas such as NLP, LLM, recommendation systems Information Retrieval stacks, GenAI (specifically RAG systems).

Familiar with architecture and implementation of 1+ ML frameworks (PyTorch, scikit-learn).

Experience working in the full model lifecycle (including experimentation, training, testing, monitoring, and deployment).

Good knowledge of AWS’s machine learning infrastructure.

Again this is a superb opportunity to join a business that truly value innovation and there will be lots of opportunity for future growth and development within this team.

If interested please send any questions to danb@burnssheehan.co.uk

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.