Senior Machine Learning Engineer

Inventure; San Francisco (CA); Hybrid; USD 200,000 - 400,000; Full time

Benefits offered by this job

Equity

Hybrid work

Remote week each month

In-office SF/NY

Job summary

Inventure in San Francisco or New York is hiring a Machine Learning Engineer to join a Series B AI company working at the frontier of model research. You will help turn cutting-edge ideas into production systems and build infrastructure for training, inference and evaluation at scale.

You’ll collaborate with researchers to deploy frontier models, optimize GPUs, and improve ML infrastructure. This hybrid role offers substantial ownership, equity, and close collaboration with a world-class team.

Qualifications

• Strong hands-on experience with PyTorch or JAX.
• Experience with distributed training or large-scale model infrastructure.
• Deep systems knowledge across distributed computing and GPU optimization.
• Ability to move between research code and production engineering.

Responsibilities

• Build and optimise infrastructure supporting training, inference and evaluation at frontier-model scale.
• Partner closely with researchers to transform novel ideas into reliable, production-ready systems.
• Work across distributed training, GPU optimisation, model performance and ML infrastructure.
• Own technically challenging projects from early research through to deployment.
• Help shape both the engineering roadmap and the research tools that enable future breakthroughs.

Skills

PyTorch

JAX

Distributed training

GPU optimisation

ML infrastructure

Production engineering

Job description

Machine Learning Engineer | Series B AI Company | Hybrid SF or NY | $200k–$400k + Equity

We're partnering with a well-funded Series B AI company (~$200M raised, $1B+ valuation) working at the frontier of foundation model research. Backed by leading investors and researchers, they're tackling some of the hardest problems in modern machine learning—not by simply building larger models, but by developing new ways to better understand, evaluate and work with them.

This is an opportunity to join a small, high-calibre team where research and engineering go hand in hand. You'll help turn cutting-edge ideas into production-ready systems, building infrastructure and tooling that enables some of the world's leading AI teams to explore, improve and deploy frontier models with greater confidence.

If you're excited by technically ambitious problems, working alongside exceptional researchers, and building technology that could shape the next generation of AI, this is the kind of opportunity that's hard to find elsewhere.

The Role

As a Machine Learning Engineer, you will:

• Build and optimise infrastructure supporting training, inference and evaluation at frontier-model scale.
• Partner closely with researchers to transform novel ideas into reliable, production-ready systems.
• Work across distributed training, GPU optimisation, model performance and ML infrastructure.
• Own technically challenging projects from early research through to deployment.
• Help shape both the engineering roadmap and the research tools that enable future breakthroughs.

The Candidate

You’ll likely have:

• Strong hands-on experience with PyTorch or JAX and modern distributed training or inference frameworks.
• Experience contributing to pre-training, fine-tuning or large-scale model infrastructure within a research lab, AI startup or leading technology company.
• Deep systems knowledge across distributed computing, GPU optimisation or ML infrastructure.
• The ability to move comfortably between experimental research code and production engineering.
• Curiosity about how large models behave internally and a desire to build systems that make them easier to study, evaluate and improve.

What's on Offer

• $200k–$400k base salary plus meaningful equity.
• The chance to work on some of the most technically challenging problems in AI today.
• Close collaboration with an exceptional research and engineering team.
• High ownership, rapid decision-making and genuine influence over both product and technical direction.
• Based in San Francisco or New York, with a five-day in-office culture and one fully remote week each month.

Machine Learning Engineer | Series B AI Company | In-office SF or NY | $200k–$400k + Equity