Skills

Python Research Training Machine Learning PyTorch Scikit-Learn TensorFlow Deep Learning Programming Databases git Azure Django Pandas FastAPI Langchain Large Language Models Keras

Job Specifications

Role: Machine Learning Engineer

Rate: £600 Inside IR35

Location: Remote (With Occasional visits)

Start Date: ASAP

Clearence: BPSS

As a Machine Learning Engineer (Conversational AI) you will:

Design and build sophisticated, agentic AI workflows using frameworks like LangChain or LlamaIndex to handle complex, multi-step user queries.
Fine-tune LLM models to improve accuracy, reduce latency, and optimize infrastructure costs.
Build LLM model evals for more stable, reliable application?that?is resilient to code?and?model changes.
Develop, review, and maintain the core application logic in Python 3 and Git, ensuring the service is robust, scalable, and maintainable.
Integrate a wide range of services, including third-party APIs and foundation models from hyperscalers like Google (Vertex AI), Amazon (Bedrock), and Microsoft (Azure AI).
Build secure and performant RESTful APIs using Python frameworks like FastAPI or Django REST Framework to connect the AI service with Back End government systems.
Work with vector databases and retrieval mechanisms to provide the AI agent with accurate, up-to-date information.
Collaborate in a multi-disciplinary team to continuously improve the agent's performance, reasoning capabilities, and reliability.

Who you are:

We're looking for people with a passion for public service and Generative AI skills to make a difference. You will have:

Proven experience building and deploying machine learning models in a production environment.
Strong programming skills and deep expertise in Python.
Hands-on experience building with agentic or RAG (Retrieval-Augmented Generation) frameworks like LangChain or LlamaIndex.
Familiarity with tools for working with Large Language Models via API or in a local context (eg HuggingFace transformers).
Practical experience using managed AI services and foundation models from a major cloud provider (eg, Amazon Bedrock, Google Vertex AI, Azure AI Services).
Experience with a major conversational AI platform (Google Dialogflow, Amazon Lex, Rasa, or similar).
A solid understanding of core Python ML libraries (Keras, scikit-learn, Pandas) and deep learning frameworks (TensorFlow, PyTorch).
Ability to explain complex technical concepts to both technical and non-technical audiences.
A humble attitude and eagerness to help and mentor others with empathy.
Ability to navigate ambiguity and prioritise effectively in dynamic environments.
Collaborating with design and user research disciplines to deliver valuable product outcomes.

Desirable (but not essential) experience:

Working with tools/interfaces for AI applications eg MCP protocol.
Training traditional ML and DL models using tools like Axolotl, LoRA, or QLoRA.
Experience with multi-agent orchestration frameworks (LangGraph, AutoGen, CrewAI)
Experience with observability and evaluation tools for LLMs such as TruLens or Helicone.
Experience with AI safety and reliability frameworks like Guardrails AI.

About the Company

We are a Digital, Data and Cloud technology consultancy, specialising in delivering solutions to clients across financial services, government, management consulting/outsourcing, media and broadcasting. Our extensive experience allows us to provide a specialised, individually tailored service backed by consultants that have industry specific knowledge to better understand your needs. Our expertise are complemented by the use of leading-edge technologies. We work with some of the UK's leading companies, as well as being reta... Know more