Jobs Companies Accurx Senior Machine Learning Engineer

Sobre este puesto de Senior Machine Learning Engineer en Accurx

Accurx · London (Shoreditch)

💬 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 to manage patient demand, and Self-Book, which lets patients schedule their own appointments in seconds. We’ve automated routine care with Patient Questionnaires for long-term conditions, while 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, 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 collaborative rigour to design and code reviews, surfacing erroneous assumptions before they reach production, and can preemptively identify technical risks — such as data leakage or hardware constraints — before they jeopardise the product roadmap.

Bonus points if you have…

  • Experience working with sensitive, regulated data (GDPR, HIPAA) and implementing privacy-first techniques like differential privacy or secure data handling.

  • Familiarity with infrastructure-as-code tools like Terraform, Kubernetes, or MLOps platforms such as SageMaker or Vertex AI.

  • Hands-on experience fine-tuning LLMs, prompt engineering, or managing the latency and cost trade-offs of large language models at scale.

What’s in it for me?

You'll be joining an established but fast-growing Tech for Good movement, where we're led by our Principles and our mission to fix healthcare communication.

  • £100,000 - £115,000 salary + share options up to £30,000

  • Benefits to suit you: adjust your healthcare cover, your pension or life insurance, whatever stage you’re at in life

  • Flexible working: We are an office first culture and ask that you’re in our (dog-friendly) Shoreditch office 3 days a week, with core hours of 10am - 4pm

  • Time off: You’ll get 28 days of holiday (plus bank holidays) and up to 4 weeks to work from anywhere per year

  • Family matters: We offer enhanced parental leave, fertility support and parental loss support

  • We have our very own Chef! Free healthy breakfasts, snacks and lunches will be provided, with the occasional sweet treat!

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Cómo se compara este salario de ML Engineer

Este puesto paga $144,771/yrpor debajo de el rango típico para los puestos de ML Engineer.

$142,475 la mediana de $205,000 $300,000

Rango típico $173,500–$250,000/yr, a partir de 739 ofertas comparables de ML Engineer en JobsRadar (salario anualizado en USD). Ver datos salariales de ML Engineer →

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