Senior Machine Learning Engineer

Overview

• Build & Iterate Fast: Design, experiment, and deploy production LLM and agentic systems. Quickly test hypotheses, optimise, and iterate based on real-world feedback and eval results.
• Own Evals: Build and maintain the evaluation harness that tells us whether a model or prompt change made things better or worse.
• Design Agentic Workflows: Architect multi-step, tool-using pipelines with explicit state, guardrails, and human-in-the-loop review where the stakes demand it.
• Lead Innovation: Push the envelope with cutting-edge LLM and agentic techniques to solve hard problems in language understanding, extraction, and reasoning.
• Shape the Product : Collaborate with Product, Design, and Underwriting SMEs to align ML capabilities with product goals and real domain constraints.
• Scale & Optimise : Take systems from prototype to production, optimising for latency, cost per run, and reliability at scale.
• Experience: 6+ years in ML/AI, with deep hands-on expertise in NLP, LLMs/SLMs, and agentic systems.
• LLMs & Architectures: Hands-on experience building with OpenAI and Anthropic models/APIs; strong knowledge of LLMs and agent architectures.
• Tooling: Practical experience with LiteLLM, vLLM, Langfuse (or equivalent LLM observability tooling). Experience with Claude Code/Codex and associated coding-agent workflows is a plus.
• Evals: Proven ability to design, build, and own evaluation harnesses for LLM/agent outputs.
• Prompt & Context Engineering: Proven ability to design and optimise prompts and context, including techniques like few-shot, chain-of-thought, and prompt tuning techniques, grounded in measurable evaluation rather than guesswork. Prior experience with  DSPy, GEPA, or similar is a plus.
• Backend & Infra Skills: Strong Python skills, with FastAPI for service development, Postgres (or similar) for data persistence, and comfort with event-driven, async architectures. Working knowledge of ML frameworks (PyTorch, TensorFlow), containerisation with Docker and Kubernetes, and cloud platforms (AWS preferred).
• Think in Outcomes: You care about whether the system actually solves the underwriter's problem, not just whether the model scores well. You're comfortable challenging the spec, proposing a different approach, and owning your feature from idea through to production impact.
• Mindset: Entrepreneurial, ownership-driven, and biased to action, with a "Build Fast, Fail Fast" approach, thriving in agile, iterative environments.
• Decision Platform - a B2B enterprise platform that provides a best-in-market Underwriting Rules Engine used by over 30 insurers to power their underwriting decisions. The product is sold across UK & Ireland, Asia-Pacific and North America. The platform combines our engine with technology to source and process third-party information supporting underwriting decisions for insurers. We are already working on capabilities, powered by AI, to make these decisions even more efficient.
• Protection Platform - a B2B2C marketplace used by over 15,000 advisors to power quoting and purcha

Job Title

Senior Machine Learning Engineer

Job Description

As a Senior Machine Learning Engineer, you’ll take ownership of designing, building, and deploying advanced LLM-based and agentic systems that extract and reason over medical records and application data. You’ll experiment, iterate, and ship quickly, working alongside a cross-functional team in a dynamic, fast-fail environment. You'll own the evals that prove your system works, and the guardrails that keep it working once real users depend on it. Your work will have a direct impact on our product and business as we push the boundaries of what’s possible with AI.

What you will be Doing

What type of person fits the role:

What we offer

Here at UnderwriteMe, you have the chance to work on solving complex problems that will change how lives are protected. This means working in an environment where you can really make a difference and where the opportunities for continuous learning and development are abound.

Unlike many other scale-up Tech companies, we have the financial backing of our successful parent company. This means we can offer a number of benefits and programmes to reward and recognise our employees’ contributions, which reflect the value we place on our employees. From competitive salaries and bonus schemes to wellness offerings and a hybrid working approach that facilitates a healthy work-life balance

We also take pride in giving back to the community and offer rewarding volunteering and social responsibility opportunities.

About UnderwriteMe

UnderwriteMe is an Insurtech software business and subsidiary of Pacific Life Re (PL Re), a global life and pensions reinsurance firm. We have a vision to help everyone purchase protection insurance by using data and disruptive technology to transform our partners and markets in order to make their underwriting processes as quick and efficient as possible.

Our core products are: