обновлено 14 дней назад
Member of Technical Staff, Machine Learning (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
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 reliable long-running workflows, persistent context, and real-world task completion. Focus on fine-tuning models, designing robust data pipelines, debugging production incidents, and optimizing latency, cost, reliability, and safety.
Location: Remote, China; address in Beijing, China. Interviews may be conducted virtually or onsite.
Company
Building proactive AI-native applications that help users manage conversations, errands, organization, 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 production systems running on GPUs.
- Implement evaluation and testing to understand model behavior.
- 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 skills.
- Experience or familiarity with PyTorch or JAX.
- Ability to work through ambiguity, learn quickly, and grow ownership over time.
- Bias toward shipping, iteration, and continuous improvement.
Culture & Benefits
- Work with a small, high-talent-density, hands-on team.
- Make decisions collectively while moving at a rapid pace.
- Balance high-quality delivery with learning from real production systems and user feedback.
- Work on practical AI products intended for users worldwide.
- Expect a prompt hiring decision after three, and no more than four, interviews.
Hiring process
- Applications are evaluated by technical team members.
- Complete three, and no more than four, interviews via virtual meetings and/or onsite sessions.
- Successful candidates receive a prompt offer decision.
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