openashbyhqatomico
Senior Machine Learning Engineer
AccuRx
LocationLondon (Shoreditch)
WorkplaceHybrid
EmploymentFullTime
Posted2026-04-22T16:44:42.639+00:00
Last observed2026-06-13 05:24:15.263165
Job idatomico-accurx:ashbyhq:0186ef38-f429-4b14-881c-32b426a6cec2
💬 ACCURX IS WHERE CONVERSATIONS HAPPEN WITH AND ABOUT PATIENTS. For decades, the NHS has struggled with fragmented systems that make simple tasks feel impossible. We’re changing that by building a single, system-wide platform that connects everyone through communication. What started as a way for GPs to text a patient has now evolved into an all-in-one digital toolkit used by 98% of GP practices. Our platform now powers Total Triage https://www.accurx.com/primary-care to manage patient demand, and Self-Book, https://www.accurx.com/booking which lets patients schedule their own appointments in seconds. We’ve automated routine care with Patient Questionnaires https://www.accurx.com/questionnaires for long-term conditions, while Accumail https://www.accurx.com/accumail finally allows staff-to-staff communication to happen instantly across different care settings. We’re now pushing the boundaries of the consultation itself with Accurx Scribe https://www.accurx.com/scribe, our AI-powered note-taker that drafts medical notes in real-time. THE TEAM We are a mission-driven team of 80 engineers based in London and the surrounding areas, united by the challenge of fixing healthcare communication. We are innovating for the NHS at a scale and depth that has never been done before, solving the real-world problems that stand between millions of patients and the care they need. We are a highly cross-functional group where engineering, product, data, and security collaborate as true peers. We foster a low-ego, high-impact environment that values expertise and new ideas, maintaining the high standards required to build and scale a national healthcare communication platform. As a Senior Machine Learning Engineer, you'll join our Triage Intelligence team — a high-impact, cross-functional group of software engineers, Data Scientists, clinicians, and a Principal Product Manager. The team builds the intelligence that powers how Accurx understands healthcare communication across the entire product suite, with a current mission to interpret patient healthcare requests and enable fast, informed decisions about the next step in a patient's care. CHALLENGES YOU’LL SOLVE... - You will take ownership of the end-to-end technical design of ML systems - from data ingestion and training pipelines through to deployment and real-time monitoring - ensuring AI features are performant, observable, and easy to debug. - You will act as the primary technical partner to our Data Scientists, evolving experimental code into high-quality, extensible library modules and building reusable components that improve developer efficiency and reduce cycle times across the team. - You will translate complex clinical and product objectives into efficient computational tasks, selecting the right tools - whether Deep Learning, NLP, or off-the-shelf - and making smart build-vs-buy trade-offs that align with Accurx's long-term technical goals. - You will help turn one-off experiments into repeatable platform capabilities, building models and systems that can be adopted by other Accurx product teams and proactively resolving cross-team dependencies as new, more efficient AI models are rolled out. YOU SHOULD APPLY IF... - You have extensive experience with a variety of ML techniques (e.g. Transformer-based NLP, Deep Learning, Tree-based methods, Bayesian modelling) and the ability to select the right tool, not just the trendiest one, for a clinical problem. - You have a proven track record of taking models from a Jupyter notebook to a high-availability production environment, managing everything from data versioning to model serving. - You have mastery of a production-grade language (e.g. Python, C#, or Go), with a focus on writing extensible, modular libraries that other teams can adopt. - You have experience defining both offline metrics (how the model performs in training) and online metrics (how the model impacts real-world user behaviour and triage outcomes). - You bring collabor...
This page is generated from the committed OpenOpps static snapshot. Use the source posting or apply link for the employer's current canonical posting state.