Machine Learning Engineer

About the Role

We’re looking for a Machine Learning Engineer to design, build, and optimise next-generation Conversational AI systems that power intelligent, human-like digital assistants across the public sector. This is a permanent position offering remote working and flexibility with occasional client visits, expenses covered.

You’ll work on agentic AI workflows , fine-tune large language models , and ensure our systems are reliable, explainable, and secure - directly contributing to innovations that help government services run smarter and faster.

What You’ll Do

• 🧠 Design & Build: Develop agentic AI workflows using frameworks like LangChain or LlamaIndex for complex, multi-step reasoning.
• ⚙️ Model Optimisation: Fine-tune LLMs to improve accuracy, reduce latency, and lower infrastructure costs.
• 🧪 Evaluation & Reliability: Build robust model evaluation frameworks to ensure consistency across model and code changes.
• 🧩 Core Engineering: Develop scalable backend services in Python 3 with Git , FastAPI , or Django REST Framework .
• ☁️ Cloud Integration: Work with Google Vertex AI , Amazon Bedrock , and Azure AI to integrate foundation models and APIs.
• 🗂️ Contextual Retrieval: Use vector databases and retrieval systems to enhance contextual understanding.
• 🤝 Collaboration: Partner with data scientists, engineers, and designers to continuously improve agent performance and reasoning.

Who You Are

You’re a hands-on engineer who’s excited by the intersection of AI, language, and systems engineering - someone who thrives in a collaborative, mission-driven environment.

You bring:

• Proven experience deploying machine learning models into production environments.
• Strong Python skills and experience with LLM frameworks (LangChain, LlamaIndex, HuggingFace Transformers).
• Knowledge of conversational AI platforms (Dialogflow, Lex, Rasa).
• Familiarity with TensorFlow , PyTorch , Keras , scikit-learn , and Pandas .
• Experience integrating with cloud-based AI services (AWS, Google Cloud, Azure).
• The ability to communicate complex technical concepts clearly and confidently.

Desirable (Not Essential)

• Experience with AI application interfaces (MCP protocol).
• Knowledge of multi-agent orchestration (LangGraph, AutoGen, CrewAI).
• Familiarity with AI safety and observability tools (TruLens, Helicone, Guardrails AI).
• Experience with Axolotl , LoRA , or QLoRA fine-tuning methods.

Why Join Us

• 💡 Work on cutting-edge AI systems that make a tangible difference in how public services are delivered.
• 🌍 Fully remote , flexible culture.
• 🧭 Contribute to meaningful projects in science, innovation, and technology.
• ⚡ Rapid, 1-stage interview process — no bureaucracy, just great conversations.