Top AI & Machine Learning Jobs

Develop and optimize AI models for specialized hardware, collaborating with research and software teams to enhance performance across large-scale systems.

Lead cross-functional programs for AI networking infrastructure, ensuring alignment between network architecture, hardware development, and operational readiness. Manage supplier relationships and oversee the technical roadmap for scalable AI infrastructure delivery.

The PyTorch Engineer will design, implement, and optimize features for machine learning frameworks, ensuring high performance and code quality while supporting users and collaborating with teams.

The AI Platform Architect will design a cohesive architecture for AI environments, oversee workload orchestration, eliminate system bottlenecks, and collaborate on hardware-software integration. Responsibilities include developing a 3-to-5-year technical vision for the AI platform and ensuring data flow between AI compute nodes and network fabrics is optimized.

As a Senior Machine Learning Engineer, you will develop and optimize AI models, conduct experiments, and collaborate with teams on advanced AI hardware projects.

The role involves testing, validating, and benchmarking ML software, focusing on performance, reliability, and correctness. It requires collaboration on ML frameworks and infrastructure, developing automated testing tools, and owning testing aspects and innovation.

The Staff Engineer (ML Engineer) will benchmark ML models, validate frameworks, develop automated testing pipelines, and collaborate with software teams to ensure performance and correctness of ML systems.

The role involves testing, validating, and benchmarking ML software systems, focusing on performance and reliability, while collaborating with software and hardware teams.

The role focuses on validating and benchmarking ML software stacks, ensuring performance and reliability across various AI workloads. Responsibilities include analyzing benchmarks, maintaining testing pipelines, and collaborating with software teams on feature testing.

The Senior ML Engineer will test and benchmark ML software stacks, validate performance, and collaborate with software teams, focusing on building automated testing pipelines.