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AI Engineer (LLMs, Agents & Applied Data Science)
Talan
London, GBR
Full-time
Entry · 2+ years experience
Hybrid
Discovered 2 weeks ago
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Required skills & experience
- Build, test, and deploy AI and machine learning components within client projects to the standards and designs set by senior colleagues.
- Develop GenAI and LLM-based features (prompting, retrieval-augmented generation, and simple agentic workflows) alongside more traditional ML models.
- Deliver classical data science tasks (data preparation, feature engineering, model training, and evaluation) on projects that call for them.
- Translate solution designs into clean, well-documented, production-minded code.
- Contribute to model evaluation, testing, and monitoring.
- Support and guide very junior and graduate resources, reviewing their work and helping them grow.
- Help peers unblock technical problems and share knowledge across the team.
- Take part in client and team discussions and communicate your work clearly.
To qualify for this role, you must have
- Typically, 2–4 years' experience in data science, machine learning, or AI engineering.
- Solid grounding in core data science and machine learning.
- Practical experience with LLMs and generative AI, including prompting and RAG.
- Familiarity with how AI agents are built and orchestrated.
- Strong Python and common data/ML libraries; good engineering habits.
- Clear communicator and collaborative team player.
Ideally, you’ll also have, but not essential
Exposure to cloud AI platforms, Azure a plus.
Experience practicing MLOps and LLMOps.
Early experience mentoring junior colleagues.
Interest in consulting and client-facing delivery.
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