Machine Learning Engineer
- London, United Kingdom
Posted 7 days ago
About the role
Company Description
AI Gen Apps builds generative AI-powered applications that help businesses create, automate, and scale digital products faster. We combine large language models, retrieval systems, and modern software engineering to ship production-ready AI features for our clients. Our team collaborates across time zones in a fast-paced, experimentation-driven environment where new ideas are tested quickly and iterated on often.
Role Description
We're looking for a Machine Learning Engineer to design, build, and deploy generative AI applications, including LLM-powered features, retrieval-augmented generation (RAG) pipelines, and AI agents. You'll work closely with product and engineering teams to take ideas from prototype to production, fine-tune and evaluate models, optimize inference performance and cost, and monitor models once they're live. This is a full-time, remote role based in the London area.
Responsibilities
Design, build, and deploy generative AI applications and LLM-powered features end-to-end, from prototype to production.
Build and maintain RAG pipelines, prompt engineering workflows, and AI agent systems.
Fine-tune, evaluate, and benchmark large language models and other generative models for accuracy, latency, and cost.
Collaborate with product, engineering, and design teams to translate business needs into working AI features.
Monitor deployed models in production, troubleshoot issues, and continuously improve performance and reliability.
Maintain clear documentation of models, pipelines, and experiments.
Qualifications
Experience building and deploying machine learning or generative AI applications in production.
Hands-on experience with LLMs (e.g., OpenAI, Anthropic, or open-source models) and frameworks such as LangChain or LlamaIndex.
Strong Python skills and familiarity with ML frameworks (PyTorch, TensorFlow, or scikit-learn).
Experience with RAG, vector databases, prompt engineering, or fine-tuning techniques.
Understanding of MLOps practices and cloud platforms (AWS, GCP, or Azure).
Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field, or equivalent practical experience.
Ability to work independently and communicate clearly in a remote, distributed team.
Salary & Benefits
Salary range: £100,000-£150,000 per year, depending on experience.