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4 months ago

Member of Technical Staff - ML Training Systems

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 13 hours agoStatus: Live

Job Summary

We are seeking an experienced engineer to contribute to training production machine learning models and evolve Modal’s infrastructure for scalable language model training. You’ll work on open-source projects, optimize data loading and compute overlap, and collaborate with a fast-growing AI infra team across NYC and SF offices to push production ML workloads from prototype to deployment.

Location: New York, San Francisco

Workplace: Onsite

Employment Type: Full time

Job Function: Education & Training

Key Responsibilities

•Contribute to training production machine learning models and evolve infrastructure for scalable language model training.
•Collaborate with open-source projects and the broader Modal team to advance AI training capabilities.
•Identify and optimize data loading bottlenecks and overlap communications with compute to improve training performance.
•Assist with in-person collaboration in NYC or San Francisco offices and participate in cross-functional discussions with researchers and engineers.
•Document approaches and share learnings to help scale ML training across teams.

Pay and Benefits

Salary: USD 150,000 - 350,000 annually

Equity and Bonus:Equity

Perks:Equity

Key Requirements

•5+ years of experience writing high-quality, high-performance code.
•Experience working with torch and high-level training frameworks (Huggingface, verl, slime)
•Experience with ML training optimization (e.g., eliminating data loading bottlenecks, overlapping communications with compute, rewriting a trainer for off-policy rollouts)
•Nice-to-have: familiarity with low-level operating system foundations (Linux kernel, file systems, containers, etc)
•Ability to work in-person, in our NYC or San Francisco office.

Experience:5+ yearsAI infrastructureMachine learningOpen source

Skills:CommunicationTeamworkProblem-solving

Tech Stack:PyTorchHugging FaceTorchLinuxContainersDocker

Company Brief

Modal

Provides a serverless, high-performance cloud platform for AI, ML, and data workloads — offering instant autoscaling, elastic GPU access, and developer-first tooling to run inference, training, and batch jobs at scale.

Industry: Cloud Computing

Company Size: Small (11 to 50 employees)

Growth: Growth Stage Startup

Valuation: Unicorn (USD 1B+)

Funding: Series B

Headquarters: New York City, United States

Founded: 2021

Website LinkedIn

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Modal

4 months ago

Member of Technical Staff - ML Training Systems

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 13 hours agoStatus: Live

Job Summary

Location: New York, San Francisco

Workplace: Onsite

Employment Type: Full time

Job Function: Education & Training

Key Responsibilities

•Contribute to training production machine learning models and evolve infrastructure for scalable language model training.
•Collaborate with open-source projects and the broader Modal team to advance AI training capabilities.
•Identify and optimize data loading bottlenecks and overlap communications with compute to improve training performance.
•Assist with in-person collaboration in NYC or San Francisco offices and participate in cross-functional discussions with researchers and engineers.
•Document approaches and share learnings to help scale ML training across teams.

Pay and Benefits

Salary: USD 150,000 - 350,000 annually

Equity and Bonus:Equity

Perks:Equity

Key Requirements

•5+ years of experience writing high-quality, high-performance code.
•Experience working with torch and high-level training frameworks (Huggingface, verl, slime)
•Experience with ML training optimization (e.g., eliminating data loading bottlenecks, overlapping communications with compute, rewriting a trainer for off-policy rollouts)
•Nice-to-have: familiarity with low-level operating system foundations (Linux kernel, file systems, containers, etc)
•Ability to work in-person, in our NYC or San Francisco office.

Experience:5+ yearsAI infrastructureMachine learningOpen source

Skills:CommunicationTeamworkProblem-solving

Tech Stack:PyTorchHugging FaceTorchLinuxContainersDocker

Company Brief

Modal

Industry: Cloud Computing

Company Size: Small (11 to 50 employees)

Growth: Growth Stage Startup

Valuation: Unicorn (USD 1B+)

Funding: Series B

Headquarters: New York City, United States

Founded: 2021

Website LinkedIn