Roblox предлагает четко очерченную роль principal-уровня, зарплату выше рыночного ориентира и работу над инфраструктурой для миллиардов ML-инференсов. Главные ограничения - офисный формат в Сан-Матео и возможные ограничения по визовой поддержке.
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Ограничения по визеЗарплата выше рынкаЧеткие задачиAI в большом масштабеРабота из офиса
Оценка от Hirify AI
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Текст:
Hirify AI/Оригинал
TL;DR
Principal Machine Learning Platform Engineer (Foundation AI) (ML platform/infrastructure): Building durable APIs, SDKs, CLIs, and UIs for a high-scale ML platform supporting model training, evaluation, deployment, and operation with an accent on developer experience, reliability, and GPU-intensive workloads. Focus on designing serving layers, model registries, pipeline orchestration, and training/inference control planes while setting technical strategy, improving platform adoption, and mentoring engineers.
Location: San Mateo, California, United States. Office-based roles are onsite Tuesday through Thursday, with optional presence on Monday and Friday.
Salary: $295,250–$345,050 USD annual base pay.
Company
Roblox builds tools and platforms for developers and creators to produce immersive 3D digital experiences.
What you will do
Own the ML platform as a product, defining requirements and delivering APIs, SDKs, CLIs, and UIs.
Build and maintain the serving layer, model registry, pipeline orchestrator, and training and inference control planes.
Set technical strategy for scalable infrastructure with clear latency, availability, and cost objectives.
Create templates, golden paths, opinionated defaults, and documentation that reduce time to production.
Measure platform adoption, usability, reliability, and cost, and use the data to prioritize improvements.
Partner with ML Engineering, Data Science, Infrastructure/SRE, Security, and Finance teams; lead architecture decisions and mentor engineers.
Requirements
10+ years of professional experience with extensive system design experience.
Strong hands-on software engineering experience and a record of shipping internal developer platforms.
Proficiency in API design and developer experience, including gRPC or REST APIs, SDKs, CLIs, and user interfaces.
Experience with infrastructure as code, automation, and reliable high-scale systems.
Clear written and verbal communication skills, including collaboration across technical disciplines.
Bachelor’s degree in Computer Science, Computer Engineering, Data Science, or a related technical field.
Nice to have
Experience with the end-to-end machine learning model lifecycle, including model serving, training, model CI/CD, and GPU resource management.
Culture & Benefits
Work on ML infrastructure supporting hundreds of use cases and billions of inferences per day.
Collaborate across ML, data, infrastructure, security, and finance organizations.
Full-time employees are eligible for equity compensation and company benefits.
For US-based roles, certain US visa categories may not be supported, and future H-1B sponsorship may not be available.
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