About the Role
About Rivian
Rivian is on a mission to keep the world adventurous forever. This goes for the emissions-free Electric Adventure Vehicles we build, and the curious, courageous souls we seek to attract.
As a company, we constantly challenge what's possible, never simply accepting what has always been done. We reframe old problems, seek new solutions and operate comfortably in areas that are unknown. Our backgrounds are diverse, but our team shares a love of the outdoors and a desire to protect it for future generations.
Role Summary
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.
Responsibilities
• Model Optimization: Develop and deploy ultra-low latency Deep Learning and Machine Learning algorithms specifically tailored for Rivian ADAS and Autonomy use cases.
• Hardware-Aware Design: 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.
• Performance Profiling: Utilize and automate deep-dive profiling tools (e.g., Torch Profile, NVIDIA Nsight) to identify bottlenecks and ensure performance consistency across weekly evaluation runs.
• Cross-Functional Collaboration: 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.
• Architectural Reasoning: Apply a deep understanding of GPU architectures to optimize models across significantly different hardware targets, ensuring scalability across the Rivian fleet.
• Workflow and Infrastructure Engineering: Design and build automated pipelines for regular model profiling across diverse architectures to enhance organization-wide insight into execution bottlenecks.
Qualifications
• Education/Experience: 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.
• Core ML Expertise: Deep understanding of modern model architectures, including Transformers, LLMs, VLMs and LDMs.
• Optimization Skills: Proven experience in model compression techniques: knowledge distillation, pruning, and quantization (PTQ/QAT).
• Hardware Knowledge: In-depth understanding of GPU architecture and the ability to optimize for diverse hardware specifications.
• Technical Toolset: ○ 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.
• Leadership: Strong team player with excellent communication skills to drive complex, cross-functional efforts in a fast-paced environment.
How To Distinguish Yourself
○ 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.
Pay Disclosure
Salary Range for California Based Applicants: $228,000 - $285,000 (actual compensation will be determined based on experience, location, and other factors permitted by law).
Benefits Summary: Rivian provides 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, and Rivian overs most of the premiums.
Equal Opportunity
Rivian is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, sex, sexual orientation, gender, gender expression, gender identity, genetic information or characteristics, physical or mental disability, marital/domestic partner status, age, military/veteran status, medical condition, or any other characteristic protected by law.
Rivian is committed to ensuring that our hiring process is accessible for persons with disabilities. If you have a disability or limitation, such as thos