2 часа назад
Software Engineer (AI Infrastructure)
226 000 - 283 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Software Engineer (AI Infrastructure): Building developer tooling, MLOps capabilities, and highly available platform services on Ray for distributed AI workloads with an accent on agent-first interfaces, observability, and production model serving. Focus on designing scalable CLI, SDK, API, and MCP surfaces, operating backend services across cloud environments, and simplifying the path from local code to reliable distributed execution.
Location: San Francisco, United States; hybrid work
Target base salary: $226,000–$283,000 annually, plus equity.
Company
develops a platform based on Ray that enables developers and data scientists to scale machine learning applications from laptops to distributed clusters.
What you will do
- Build developer tooling and MLOps capabilities on Ray for developers and coding agents.
- Develop agent-first CLI, SDK, API, and MCP interfaces with self-discovery, structured errors, dry-run support, and consistent resource behavior.
- Improve the workflow from local code to distributed execution across environments, dependencies, images, authentication, submission, and debugging.
- Build tools for the AI development lifecycle, including data preparation, fine-tuning, evaluation, serving, dataset management, experiment tracking, and lineage.
- Design model registration, deployment, benchmarking, and observability capabilities for reliable production endpoints.
- Design and operate highly available backend services and platform architecture across serverless and bring-your-own-cloud environments.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
- 5+ years of experience writing high-quality production code.
- Strong knowledge of algorithms, data structures, and system design.
- Experience with modern machine learning tooling such as PyTorch, MLflow, and data catalogs.
- Hands-on experience building and operating highly available production services.
- Strong product judgment and a record of shipping developer-facing tools.
Nice to have
- Experience building and maintaining open-source projects.
- Experience operating machine learning infrastructure or highly available serving systems in production.
- Experience using Ray.
Culture & Benefits
- Work directly with users and field teams to identify problems, shape designs, and iterate on products.
- Collaborate with distributed systems and machine learning experts.
- Stock options and healthcare plans with premiums covered at 99% by .
- 401(k) retirement plan, wellness and education stipend, paid parental leave, fertility benefits, and paid time off.
- Commute reimbursement and fully covered in-office meals.
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