Machine Learning Engineer (Conversational AI)
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Clearance: BPSS Eligible
Start: ASAP
Work pattern: Hybrid
Work type: 12 month FTC (Competitive Salary)
Amber Labs are supporting a major government programme focused on transforming public services through the use of AI and automation. This programme is shaping how people interact with digital services across departments — improving accessibility, efficiency, and user experience.
We’re looking for a Machine Learning Engineer (Conversational AI) to help design and build advanced conversational and agentic AI solutions. You’ll work with multi-disciplinary teams to deliver innovative AI-driven tools and services that make a real impact on the public sector.
Key Responsibilities:
* Design and develop conversational AI workflows using frameworks such as LangChain or LlamaIndex.
* Fine-tune and optimise Large Language Models (LLMs) for performance, accuracy, and cost efficiency.
* Build evaluation pipelines to ensure model reliability and stability.
* Develop secure and scalable Python applications and RESTful APIs (FastAPI, Django REST Framework).
* Integrate AI services and foundation models from providers such as Azure AI, Amazon Bedrock, and Google Vertex AI.
* Work with vector databases and retrieval mechanisms to enhance accuracy and context.
* Collaborate with data, design, and engineering teams to improve model reasoning and user experience.
Skills & Experience:
* Strong hands-on experience deploying ML models in production environments.
* Excellent programming skills in Python and familiarity with ML/DL libraries (TensorFlow, PyTorch, scikit-learn, Pandas).
* Practical experience with RAG or agentic AI frameworks (LangChain, LlamaIndex).
* Experience working with LLM APIs (e.g. Hugging Face, OpenAI).
* Exposure to conversational AI platforms (Dialogflow, Lex, Rasa, etc.).
* Ability to work collaboratively in fast-paced, agile, and multidisciplinary environments.
* Excellent communication skills and a strong interest in the application of AI in public services.
Desirable:
* Experience with multi-agent orchestration (LangGraph, AutoGen, CrewAI).
* Familiarity with AI observability tools (TruLens, Helicone).
* Awareness of AI safety and reliability frameworks (Guardrails AI).
* Experience working in government or public sector digital projects.