Machine Learning Engineer

About Our Client

Our client is a seed-stage, AI-native SaaS company backed by a top-tier accelerator and a group of respected angel investors. A small, senior founding team is embedding applied machine learning into a fast-moving product, working at the frontier of LLMs and applied NLP. Equity upside is significant and early hires will shape both the product and the engineering culture from the ground up. The company is kept confidential at this stage; full details, including the client name, are shared with shortlisted candidates.

Job Description

Our client is hiring a Machine Learning Engineer to take models from research through to reliable, production-grade features at the core of an AI-native product. This is a hands-on role that spans data, modelling and software engineering: you'll work with LLMs, retrieval and applied NLP, and you'll own the path from experiment to shipped capability. As an early technical hire, you'll help define how ML is built, evaluated and operated at the company.

• Design and build data pipelines, training workflows and evaluation frameworks
• Take models and ML capabilities from prototype to reliable production features
• Work hands-on with LLMs, retrieval-augmented generation (RAG) and applied NLP techniques
• Define and track meaningful offline and online evaluation metrics
• Partner with product to turn research and experimentation into shipped, valuable features
• Own the software-engineering quality of ML systems — testing, monitoring, CI/CD and cost
• Instrument, monitor and continually improve model performance in production
• Contribute to the overall architecture of the ML platform and inference stack
• Help establish ML best practices and mentor as the team grows

The Successful Applicant

We're looking for an engineer who combines genuine ML depth with strong software-engineering discipline, and who wants to build real products rather than just prototypes.

• 4+ years of ML / MLE experience, including shipping models to production
• Strong Python and hands-on experience with modern ML frameworks (PyTorch or TensorFlow)
• Practical experience with LLMs, RAG or applied NLP
• Solid software-engineering fundamentals — testing, version control, CI/CD
• Experience building data and training pipelines
• Comfortable with evaluation, experimentation and reasoning about model quality
• Able to work autonomously in an early-stage, fast-moving environment
• Familiarity with cloud infrastructure and model deployment is a plus

What's on Offer

This is a high-impact role at a well-backed US business, with a package built to attract and retain exceptional people: