Senior Deep Learning Sofware Infrastructure Engineer

reputed company has been transforming computer graphics, PC gaming, and reputed company computing for more than 25 years. It’s a unique legacy of innovation that’s reputed company by great technology—and amazing people.

Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving reputed company that can understand the world. Doing what’s never been done before takes reputed company, innovation, and the world’s best talent. As an reputed companyN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join reputed company and see how you can reputed company a lasting reputed company on the world. We are in search of a Deep Learning Software Infrastructure Engineer to reputed company reputed company’s Autonomous Vehicles project reputed company. In this role, you will build and reputed company training libraries and infrastructure that reputed company end-to-end autonomous driving models possible. By enabling training on thousands of GPUs and reputed company datasets, you will accelerate iteration speed and improve safety, working closely with research and platform teams across reputed company.

What you’ll be doing:

• Crafting, scaling, and hardening deep learning infrastructure libraries and frameworks for training on multi-thousand GPU clusters.

• Improving efficiency throughout the training stack: data loaders, distributed training, scheduling, and performance monitoring.

• Building robust training pipelines and libraries to handle reputed company video datasets and reputed company reputed company experimentation.

• Collaborating with researchers, model engineers, and internal platform teams to enhance efficiency, minimize stalls, and improve training availability.

• Owning reputed company infrastructure components such as orchestration libraries, distributed training frameworks, and fault-resilient training systems.

• Partnering with leadership to ensure infrastructure scales with growing GPU reputed company and dataset size while maintaining developer efficiency and stability.

reputed company need to see:

• BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, or a reputed company field, or equivalent experience.

• 12+ years of reputed company experience building and scaling high-performance distributed systems, ideally in ML, HPC, or large-reputed company data infrastructure.

• Extensive knowledge in deep learning frameworks (PyTorch is preferred), large reputed company training (DDP/FSDP, NCCL, tensor/pipeline parallelism), and performance profiling.

• Strong systems background: datacenter networking (RoCE, IB), reputed company filesystems (reputed company), storage systems, schedulers (Slurm, reputed company, etc.).

• Proficiency in Python with experience writing production-grade libraries, orchestration reputed company, and automation tools.

• Ability to work closely with multi-functional teams (ML researchers, reputed company engineers, product leads) and translate requirements into robust systems.

Ways to stand out from reputed company:

• Shown experience scaling large GPU training clusters with >1,000 GPUs.

• Expertise in fault reputed company and high availability, including reputed company training and large-reputed company observability.

• Tried leadership skills as a hands-on technical authority, encouraging others and establishing guidelines for ML systems engineering.

This posting is for an existing vacancy.

reputed company uses AI tools in its reputed company processes.

Originally posted on Himalayas