AI Runtime Engineer

AI Runtime Engineer

Location: Bangalore (or as per requirement)

Experience: 7+ years

Choosing Capgemini means joining a team where youll be empowered to build cutting-edge AI infrastructure, supported by a collaborative global community, and inspired to reimagine whats possible. Join us in enabling scalable, fault-tolerant AI systems that power next-generation machine learning workloads.

Your Role

As an AI Runtime Engineer , you will design and optimize distributed AI runtimes that enable high-performance, multi-node, multi-GPU training at scale. Youll work closely with AI infrastructure teams to build elastic, fault-tolerant systems and ensure seamless orchestration for advanced AI workloads.

In this role, you will:

• Architect and implement distributed AI runtime systems with elastic scaling and job recovery.
• Optimize performance at low levels (CUDA, NCCL, PyTorch internals) for multi-GPU workloads.
• Develop custom runtime architectures for large-scale AI training pipelines.
• Integrate orchestration tools like Kubernetes, Ray, TorchElastic, Horovod for containerized AI workloads.
• Implement fault recovery mechanisms and observability hooks for runtime health monitoring.
• Collaborate with AI researchers and platform engineers to ensure efficient resource utilization and throughput optimization.
• Contribute to CI/CD pipelines for AI infrastructure and runtime deployments.

Your Profile

Mandatory Skills:

• Hands-on experience in distributed training systems , multi-node/multi-GPU orchestration.
• Expertise in PyTorch internals , CUDA, NCCL, and performance profiling.
• Strong knowledge of Kubernetes , containerization, and orchestration frameworks.

Preferred Skills:

• Experience with TorchElastic , Ray, Horovod.
• Open-source contributions to PyTorch or runtime libraries.
• Background in HPC, compilers, or systems research .

Education:

• Bachelors/Masters in Computer Science, Engineering, or related field.