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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI/ML Performance Engineer - **Company:** General Motors - **Location:** Sunnyvale, CA, United States - **Experience:** Expert - **Salary:** $144,700.0 - $261,300.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Software Applications, Systems Engineering, Microsoft Azure, Big Data, BigQuery, Cloud Computing, Profiling, Software Debugging, Distributed Systems, Python (Programming Language), Machine Learning, Open Source Technology, Performance Tuning, Cloud Platform System, Pytorch, Grafana, Containerization, Kubernetes, Information Technology, HuggingFace, Data Analytics, Machine Learning Operations, Software Coding - **Published:** July 9, 2026 - **Apply:** https://www.juju.com/job/00000000geskt5 ## About the Role + **Experience:** 5+ years of professional experience in high-scale infrastructure or ML systems. + **Education:** Bachelor's Degree in Computer Science, a related technical field, or equivalent practical experience. + **Software Proficiency:** Expert-level coding skills in **Python** and the ability to architect/debug within the **PyTorch** ecosystem. + **Systems Engineering:** Proventrack recordof resolving performance issues within large-scale distributed production environments. + **Architectural Knowledge:** Deep understanding of distributed systems, specifically modern ML system design and high-performance computing (HPC). + **Containerization:** Hands-on experience with **Kubernetes** for orchestrating complex workloads. + **GPU Monitoring:** Technicalproficiencywith **Nvidia DCGM** , **nvidia-smi** , and **Grafana** for real-time telemetry and observability. + **Cloud Platforms:** Extensive experience working within major cloud ecosystems ( **AWS, GCP, or Azure** ). What** **w** **ill** **g** **ive** **y** **ou** **a** **c** **ompetitive** **e** **dge (Preferred Qualifications)** ** ** ** + **Advanced Experience:** 8+ years of relevant industry experience. + **Hardware Expertise:** Working knowledge of Enterprise-grade Nvidia GPU architectures, including **H100, B200, and GB200** . + **Model Deployment:** Experience deploying and scaling open-source models via the **Hugging Face** ecosystem. + **Data Analytics:** Proficiencyin **BigQuery** for large-scale data analysis and reporting. + **Profiling Tools:** Practical experience utilizing **Nvidia Nsight** and **Nsight Compute** for kernel-level performance tuning. + **Soft Skills:** Strong technical communication skills with the ability to translate complex infrastructure needs into actionable business insights. **Hybrid:** This role is categorized as Hybrid. This means the successful candidate is expected to report to Sunnyvale Technical Center at minimum three days per week or at the hiring manager's discretion. Ability to sit remote in Seattle, WA until office opens. ## Description GM is looking for a Senior Performance Engineer to join the AV Capacity and Performance Engineering team in the AV Infrastructure org to support our critical efforts in developing autonomous vehicles. The mission of the AVCPE team is to provide input into large scale ML infrastructure strategy, advise on key decisions affecting our cloud budget, identify and execute optimization projects, and provide capacity planning and engineering expertise to support GM's efforts in developing autonomous vehicles (AV). What** **you'll** **be doing** **(** **Responsibilities** **) + **Strategic Infrastructure Development:** Adopt and run AVmodels tosupport GM's long-term GPU system strategy and "evergreen" infrastructure roadmap. + **Performance Optimization:** Conduct deep-dive analyses of production workloads toidentifybottlenecks and propose high-impact optimization strategies. + **Cross-Functional Collaboration:** Partner with AI/ML Research, Infrastructure Engineering, and Cloud Vendors to spearhead projects that enhance engineering velocity and cost-efficiency. + **Proactive System Scaling:** Identifyopportunities for architectural improvements to ensure the scalability and reliability of large-scale ML training and inference environments. ## Related Videos - [Developing an AI.SDK](https://www.wearedevelopers.com/videos/198-developing-an-ai-sdk) - [5 steps for running a Kubernetes environment at scale](https://www.wearedevelopers.com/videos/88-5-steps-for-running-a-kubernetes-environment-at-scale) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [All your telemetry data from any source in one place](https://www.wearedevelopers.com/videos/57-all-your-telemetry-data-from-any-source-in-one-place) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)