Software Engineer, Workload Enablement

Skills

About the Role

You will enable production workloads and end-to-end testing on new platforms. You will port inference and training workloads to new hardware, build benchmarks, stress tests, and CI-ready test harnesses, analyze performance of distributed training and inference, and partner with systems engineers and vendors.

Requirements

• BS in CS/EE or equivalent practical experience
• 5+ years in ML systems, performance engineering, distributed systems, or HPC
• Hands-on experience with PyTorch and LLM training/inference stacks
• Knowledge of distributed training concepts
• Experience with RDMA and NCCL or RCCL
• Proficiency in Python; C++/CUDA/HIP a plus
• Strong profiling and debugging skills

Responsibilities

• Port and validate inference and training workloads on new platforms
• Build benchmarks and stress tests exercising CPU, GPU, memory, networking, storage, and thermals
• Analyze collective performance and tuning across NCCL/RCCL
• Create repeatable test harnesses for CI and lab environments
• Partner with systems and fleet bring-up engineers on containerization, K8s integration, and telemetry
• Produce clear bug reports and minimal repros for vendors and stakeholders

Benefits

• Equity
• Performance-related bonus
• Medical, dental, and vision insurance with HSA employer contributions
• Health FSA, Dependent Care FSA, and commuter pre-tax accounts
• 401(k) with employer match
• Paid parental leave up to 24 weeks for birth parents and 20 weeks for non-birthing parents
• Paid medical and caregiver leave up to 8 weeks
• Flexible PTO for exempt employees
• 13+ paid company holidays and company office closures
• Paid sick or safe time
• Mental health and wellness support
• Employer-paid basic life and disability coverage
• Annual learning and development stipend
• Daily meals in offices and meal delivery credits
• Relocation support
• Charitable donation matching and wellness stipends