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 management, and performance optimization.
• Experience with Kubernetes orchestration, resource scheduling for large distributed jobs, and containerized deployment pipelines.
• Ability to debug and optimize bottlenecks across GPU memory hierarchy, networking fabric, filesystems, and multi-GPU operations.
• Ability to reason from first principles and optimize systems for both memory-bound and compute-bound workloads.
• Strong cross-functional communication skills, ownership, and a growth mindset.

Nice to Have

• Hands-on experience with distributed training frameworks and techniques such as PyTorch DDP/FSDP, DeepSpeed, Megatron, or NCCL.
• Hands-on experience with GPU kernel development.
• Experience with data engineering technologies such as Parquet, Arrow, or similar systems.

Compensation

The pay range for this position at the start of employment is expected to be between $210,000 and $300,000/year. Your exact offer may vary depending on multiple individualized factors, including job-related knowledge, skills, and experience. In addition to cash compensation, this position will also receive generous equity for this position.

Culture:

We embrace challenges and strive to make the impossible possible each day. We're not in this to do what's easy or to be mediocre. We want to create something legendary and leave our mark on the world. We're ambitious, we're gritty, we're humble and we're relentlessly resourceful in pursuit of our goals. If this sounds like you then you might be a great fit!

Nimble's Benefits

Unlimited Flexible Time Off

Enjoy the time you need to travel, rejuvenate, and connect with friends and family.

Health Insurance

Nimble provides medical, dental, and vision insurance through several premier plans and options to support you and your family.

Paid Parental Leave

Enjoy paid bonding time following a birth.

Commuter Benefits

Take the stress out of commuting with access to fully-paid parking spots.

Referral Bonus

Get a cash bonus for any friend or colleagues that you refer to us that we end up hiring.

401k

Contribute towards a 401k for retirement planning.

Equity

Be an owner in Nimble through our equity program

Link: Nimble Closes $106 Million Series C Funding Round, Scales Fully Autonomous Fulfillment with FedEx

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