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Member of Technical Staff, Machine Learning (AI)

Формат работы
hybrid
Тип работы
fulltime
Грейд
middle
Английский
b2
Страна
UK
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
Member of Technical Staff, Machine Learning (Python/PyTorch/JAX): Building and improving production ML components across data, training, evaluation, and inference with an accent on model reliability, real-world task completion, and GPU-based systems. Focus on fine-tuning models, designing robust data pipelines and evaluation systems, and debugging latency, cost, reliability, safety, and production issues.

Location: Hybrid in London, United Kingdom

Company

hirify.global is building proactive AI-native applications that help users manage conversations, errands, organisation, and workflows with minimal prompting.

What you will do

  • Build and improve ML components across data, training, evaluation, and inference.
  • Fine-tune and adapt models within larger production systems running on GPUs.
  • Implement evaluation and testing to understand model behaviour and improve reliability.
  • Build and maintain pipelines for real-world and synthetic data.
  • Debug model issues, performance problems, and production incidents.
  • Collaborate with senior ML engineers and product teams to ship iterative improvements.

Requirements

  • Strong foundations in machine learning and modern neural architectures.
  • Hands-on experience training, fine-tuning, or deploying ML models.
  • Production-quality Python development.
  • Experience or familiarity with PyTorch or JAX and production ML systems running on GPUs.
  • Ability to work through ambiguity, learn quickly, and grow ownership over time.
  • Ability to work under production constraints including latency, cost, reliability, and safety.

Culture & Benefits

  • Work in a small, high-talent-density, hands-on team.
  • Make decisions collectively while moving at a rapid pace.
  • Balance high-quality delivery with continuous learning and iteration.
  • Work directly with real production systems and user feedback from day one.

Hiring process

  • Applications are evaluated by technical team members.
  • Expect three, and no more than four, interviews conducted virtually and/or onsite.
  • Decisions are made promptly after the interview process.

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