Чётко очерченная продуктовая роль в быстрорастущей компании AI-инфраструктуры: можно отвечать за актуальную платформу обучения моделей и тесно работать с клиентами и техническими командами.
Быстрый рост
AI-инфраструктура
Понятная зона ответственности
Доступ к экспертизе
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Product Manager, Training Platform (AI) (AI training and fine-tuning): Building the developer experience for running training jobs, from environment setup and submission through scheduling, monitoring, debugging, checkpointing, and recovery, with an accent on distributed training and ML infrastructure. Focus on simplifying GPU availability, fault recovery, experiment reproducibility, and integration with model evaluation and inference deployment.
Location: Hybrid in San Francisco or New York, United States
Salary: $200K–$400K plus equity
Company
Baseten builds cloud infrastructure and developer tooling for deploying AI models, with a platform spanning inference, training, and agent execution.
What you will do
Own the product experience for AI training jobs from environment setup and submission through execution, monitoring, and recovery.
Design intuitive workflows for distributed training, including scheduling, GPU availability, logs, checkpoints, and debugging.
Partner with research and infrastructure teams to support supervised fine-tuning and reinforcement learning workloads.
Help developers recover from failures, reproduce experiments, and reduce time spent managing infrastructure.
Connect training with Loops, model evaluation, and inference deployment.
Work directly with customers to understand model training and adaptation workflows and turn insights into product improvements.
Requirements
Experience building and shipping AI/ML products or developer platforms.
Technical background in software engineering, ML engineering, research, or equivalent hands-on work.
Direct experience working with teams that train, fine-tune, or adapt machine learning models.
Strong understanding of distributed training concepts, including GPU memory, scheduling, data access, checkpointing, and fault recovery.
Familiarity with infrastructure needs for supervised fine-tuning and reinforcement learning.
Strong product instincts for developer workflows and the ability to simplify technically complex systems.
Experience partnering with researchers and engineers to take new capabilities from concept to production.
Nice to have
Hands-on experience running distributed training, building ML developer tools, or working with trainer and sampler systems for reinforcement learning.
Culture & Benefits
Competitive compensation with meaningful equity.
U.S. employees and dependents receive 100% coverage for medical, dental, and vision insurance.
Flexible PTO and a company-wide Winter Break from Christmas Eve through New Year's Day.
Paid parental leave and a fertility and family-building stipend through Carrot.
U.S. employees have access to a company-facilitated 401(k).
Exposure to ML startups and opportunities for learning and networking.
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