Если вы раньше входили через Google, сбросьте пароль для своей Gmail-почты через кнопку «Забыли пароль?» на экране входа. Затем войдите по email и новому паролю.
Если аккаунта ещё нет, зарегистрируйтесь с Gmail-почтой, после подтверждения почты мы предложим задать пароль.
Что нового
Загружаю обновления...
Что нового
Загружаю обновления...
Работа найдется быстрее с подпискойКандидат найдётся быстрее с подпиской
Чтобы адаптировать резюме под вакансию или составить сопроводительное письмо, загрузите резюме
описание
Accurx builds a system-wide healthcare communication platform for the NHS. Its digital toolkit connects healthcare professionals and patients, supporting triage, appointment scheduling, patient questionnaires, staff communication, and AI-powered medical note-taking.
задачи
Own the end-to-end technical design of ML systems, from data ingestion and training pipelines through deployment and real-time monitoring;
Partner with Data Scientists to evolve experimental code into high-quality, extensible library modules;
Build reusable components that improve developer efficiency and reduce cycle times across the team;
Translate complex clinical and product objectives into efficient computational tasks;
Select appropriate tools, including Deep Learning, NLP, and off-the-shelf solutions, and make build-versus-buy trade-offs;
Turn one-off experiments into repeatable platform capabilities;
Build models and systems that can be adopted by other Accurx product teams;
Resolve cross-team dependencies as new AI models are rolled out.
требования
Extensive experience with ML techniques such as Transformer-based NLP, Deep Learning, Tree-based methods, and Bayesian modelling;
Proven experience taking models from a Jupyter notebook to a high-availability production environment;
Experience managing data versioning and model serving;
Mastery of a production-grade language such as Python, C#, or Go;
Experience writing extensible, modular libraries for adoption by other teams;
Experience defining offline and online metrics;
Strong design and code review skills;
Ability to identify technical risks such as data leakage and hardware constraints before they affect the product roadmap;
Nice to have: experience with sensitive, regulated data and privacy-first techniques such as differential privacy or secure data handling, familiarity with Terraform, Kubernetes, SageMaker, or Vertex AI, hands-on experience fine-tuning LLMs, prompt engineering, and managing latency and cost trade-offs of large language models at scale.
условия
Share options up to £30,000;
Flexible healthcare cover, pension, and life insurance options;
Office-first culture with 3 days per week in the Shoreditch office;
Core hours are 10am - 4pm;
28 Days of holiday plus bank holidays;
Up to 4 weeks to work from anywhere per year;
Enhanced parental leave, fertility support, and parental loss support;