Senior AI/ML Ads Training Engineer

Google Inc.; Mountain View (CA); On-site; USD 174,000 - 252,000; Full time

Job summary

Google Inc. is seeking a Senior Software Engineer for AI/ML Ads Training in Mountain View, CA.

You will drive TPU efficiency for core training workloads and lead cross-stack optimizations across TensorFlow/JAX/PyTorch, enabling scalable, high-performance ads ML pipelines. You will collaborate with Google Research and DeepMind, contribute to enabling next-gen hardware, and deliver measurable efficiency gains and business impact within Ads.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience programming in Python or C++.
• 3 years of experience with ML infrastructure, ML execution frameworks (e.g., TensorFlow, JAX, PyTorch), or hardware accelerators (TPUs, GPUs).
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
• Experience with large-scale distributed systems and performance debugging.

Responsibilities

• Write and test product or system development code.
• Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
• Design and implement solutions in one or more specialized ML areas, leverage ML infrastructure, and demonstrate expertise in a chosen field.

Skills

Python

C++

ML infrastructure

ML frameworks

Distributed systems

Testing/architecture

Education

Bachelor's degree or equivalent

Job description

Google Inc. is seeking a Senior Software Engineer for AI/ML Ads Training in Mountain View, CA.

You will drive TPU efficiency for core training workloads and lead cross-stack optimizations across TensorFlow/JAX/PyTorch, enabling scalable, high-performance ads ML pipelines. You will collaborate with Google Research and DeepMind, contribute to enabling next-gen hardware, and deliver measurable efficiency gains and business impact within Ads.