Senior Machine Learning Engineer (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
TL;DR
Senior Machine Learning Engineer (PyTorch/JAX): Building core ML systems powering a proactive AI chat app for long-running workflows, multi-step reasoning, and real-world task completion with an accent on high reliability, persistent context, and external tool integration. Focus on owning end-to-end ML lifecycle including data preparation, training, evaluation, inference, debugging production failures, and rapid iteration based on real signals.
Location: Remote (United Kingdom)
Company
's A1 team is a small, high-talent-density group building a proactive AI chat app to bring intelligence to everyday conversations, errands, and workflows.
What you will do
- Build core ML systems for proactive, long-horizon AI products handling multi-step reasoning and external interactions.
- Own end-to-end ML work: data preparation, training, evaluation, inference, and iteration under production constraints.
- Turn research ideas into reliable production systems and debug failures using real signals.
- Iterate quickly by shipping, measuring outcomes, refining, and collaborating with research, product, and engineering teams.
- Mentor other ML engineers through example and technical judgment.
Requirements
- Built and shipped ML systems used by real users in production.
- Deep understanding of modern ML model behavior and misbehavior in production environments.
- Strong production-quality code with systems thinking, not just scripts.
- Proven ownership, independent execution, fast learning, and clear communication.
Culture & Benefits
- Work in small, world-class, high-talent-density teams making collective decisions at rapid speed.
- Hands-on environment balancing high-quality shipping with continuous learning.
- Emphasis on structure, judgment, and independent execution to deliver magical user products.
Hiring process
- Applications evaluated by technical team; 3-4 interviews via virtual meetings and/or onsite.
- Prompt decisions with offers extended to exceptional fits.
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