Senior​/Software Engineer, Infrastructure; ML) San Francisco, CA

Senior/Staff Software Engineer, Infrastructure (ML)

About Nimble

Nimble is an AI robotics company building the autonomous supply chain to power fast, efficient and economical commerce. We’re training robot AGI to power a proprietary generalist supply chain superhumanoid, the first robot in the world capable of performing thousands of tasks across the supply chain. We’ve raised over $220M at over $1B valuation and formed a strategic alliance with Fed Ex to build a national network of autonomous warehouses capable of generating many billions in annual revenue.

We are a hardcore and obsessed team of the world’s best engineers and operators. If you are obsessed with your craft, enjoy a high-intensity and fast moving high impact environment, are super high agency in getting hard things done and want to be part of building the world’s most legendary robotics company at the most pivotal moment in history, we want to work with you.

We are on a mission to empower and inspire mankind to accomplish legendary feats by inventing robots that liberate us from the menial. We will accomplish this by training robot AGI to invent and build the Autonomous Supply Chain – everything from the inside of factories and warehouses to your front door – powered by generalist superhumanoids.

Our founding team comes from the AI labs at Stanford and Carnegie Mellon and our board of directors include famed robotics and AI legends including Fei-Fei Li (Chief Scientist of AI at Google and Director of Stanford’s AI Lab), Marc Raibert (founder of Boston Dynamics), and Sebastian Thrun (founder of GoogleX, Waymo; Stanford Professor and considered the father of autonomous vehicles).

Let’s be legendary.

Why Join Nimble?

At Nimble, we are committed to building legendary products, a legendary team, and a legendary legacy. Join us and become part of an ambitious, humble, and resourceful culture where your work will leave a lasting impact on the future of robotics and commerce.

Nimble's Core Values:

Be relentlessly resourceful
-Challenge conventions and overcome obstacles.

Be legendary
-Be the very best and do work that inspires.

Be humble
-Prioritize growth, learning, and doing whatever is needed to further the mission.

Be dependable
-Take ownership and deliver with high agency.

About the Role

We’re looking for a Software Engineer to join our ML Infrastructure team. In this role, you’ll help build the training and inference systems that power our general-purpose warehouse robots.

You’ll own training infrastructure end to end: keeping GPUs highly utilized, making runs reproducible, and ensuring every researcher can launch the next experiment with a single command. You’ll work closely with ML and Robotics teams to design, build, and scale the systems that turn our GPU clusters into a reliable, high-throughput platform for model development.

Responsibilities

• Design, develop, and maintain ML training infrastructure that enables the AI team to run training jobs efficiently, manage and iterate experiments quickly.
• Build low-latency inference pipelines for production robotics workloads.
• Develop, tune, and optimize low-level CUDA kernels.
• Design training-platform systems for scalable model training, including high-throughput data ingestion, dataset sharding and sampling for distributed training.
• Participate in and lead design reviews with peers and stakeholders to evaluate technical tradeoffs and select appropriate technologies.
• Review code and provide feedback to uphold best practices around style, correctness, testability, performance, and maintainability.
• Contribute to documentation and educational materials, adapting content as systems and workflows evolve.
• Mentor junior engineers and help raise the technical bar across the team.

Qualifications

• Bachelor’s, Master’s, or PhD in Computer Science or a related field, or equivalent practical experience.
• 4+ years of industry experience in infrastructure, distributed systems, ML systems, robotics, or a related area.
• Experience with programming languages such as Rust, Go, Python, or C++.
• Experience with ML frameworks such as PyTorch or JAX.
• Strong understanding of distributed systems, systems programming fundamentals, memory…