Senior/Staff ML Engineer, ML Acceleration and Performance

Rivian • Palo Alto, CA

16h

About The Position

As a Staff Software Engineer for ML Optimization and Hardware Acceleration, you will be a lead member of the Autonomy team at Rivian. You will develop and optimize advanced machine learning algorithms that directly impact the safety-critical self-driving features of our category-defining vehicles. This role focuses on the intersection of cutting-edge model architectures including Transformers, LLMs, VLMs, LDMs and high-performance hardware execution. You will bridge the gap between theoretical ML research and real- time embedded deployment, ensuring our autonomy stack remains both state-of-the-art and ultra-efficient.

Requirements

• MS (+3 years of experience in deep learning, heterogeneous computing, and ML accelerators) or Ph.D. in Computer Science, Electrical Engineering, or a related field.
• Deep understanding of modern model architectures, including Transformers, LLMs, VLMs and LDMs.
• Proven experience in model compression techniques: knowledge distillation, pruning, and quantization (PTQ/QAT).
• In-depth understanding of GPU architecture and the ability to optimize for diverse hardware specifications.
• Proficiency in Python and deep knowledge of PyTorch or TensorFlow.
• Hands-on experience with TensorRT, AIMET, ONNX runtimes.
• Experience with low-level programming (CUDA kernels, C++, or BLAS subroutines) for inference logic.
• Experience with profiling tools like torch profiler and nvidia nsight.
• Strong team player with excellent communication skills to drive complex, cross-functional efforts in a fast-paced environment.

Nice To Haves

• A strong track record of publications in top-tier venues such as MLSys, ICML, NeurIPS, or ISCA.
• Significant and direct industry experience in a related domain.
• Active participation and contributions to relevant open-source projects.
• Public demonstrations of expertise, including technical talks, presentations, or live demos.

Responsibilities

• Develop and deploy ultra-low latency Deep Learning and Machine Learning algorithms specifically tailored for Rivian ADAS and Autonomy use cases.
• Research and implement hardware-aware optimization strategies, including Post-Training Quantization (PTQ), Quantization-Aware Training (QAT), kernel fusion, and model distillation to maximize throughput on embedded platforms.
• Utilize and automate deep-dive profiling tools (e.g., Torch Profile, NVIDIA Nsight) to identify bottlenecks and ensure performance consistency across weekly evaluation runs.
• Partner with low-level software and hardware architecture teams to characterize in-house ML models on embedded platforms, optimizing them within strict compute and memory constraints.
• Apply a deep understanding of GPU architectures to optimize models across significantly different hardware targets, ensuring scalability across the Rivian fleet.
• Design and build automated pipelines for regular model profiling across diverse architectures to enhance organization-wide insight into execution bottlenecks.

Benefits

• Robust medical/Rx, dental and vision insurance packages for full-time employees, their spouse or domestic partner, and children up to age 26.
• Coverage is effective on the first day of employment.
• Rivian covers most of the premiums.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior