Senior Distributed ML Engineer

Responsibilities

• Collaborate with researchers to accelerate research, model training and inference, and facilitate the use of large-scale models in distributed computing environments
• Investigate performance bottlenecks, profile research experiment code, debug reported issues, and optimize the utilization of computing resources
• Develop tools and libraries to simplify and orchestrate the use of distributed computing resources for research experiments
• Establish, document, and maintain best practices for large-scale, distributed ML model development workflows

Requirements

• Degree in computer science, computer engineering, or software engineering
• 3+ years of experience in designing and implementing distributed ML training frameworks
• Experience with Megatron, DeepSpeed, HuggingFace Accelerate, FSDP, vLLM, or verl
• Experience with cloud platforms (AWS, GCP, Azure) and workload managers (Ray, SLURM)
• Experience with GPU profiling tools (PyTorch profiler, PyProf, NVIDIA Nsight)
• Familiarity with containerization tools (gRPC, Docker, Kubernetes)
• Familiarity with data infrastructures and platforms (vector databases)
• Track record of contributing to high-quality research projects in deep learning

Preferred Qualifications

• Advanced degree (master’s or PhD) related to machine learning or distributed ML systems

Benefits

• Comprehensive health benefits including mental health and wellness management account
• 20 days of vacation per year upon start
• 4% employer contribution to retirement savings
• Additional 8% compensation for retirement savings or bonuses

About the Company

LawZero is a non-profit organization committed to advancing research and creating technical solutions that enable safe-by-design AI systems. Based in Montreal, LawZero’s research aims to build non-agentic AI that learns primarily to understand the world rather than to act in it.