Rivian
Auto · EVs
- HQ
- Detroit, US
- Founded
- 2009
- Website
- rivian.com
Auto · EVs
Rivian currently has 8 active AI-related job listings. The majority of these roles, 50%, are focused on agents, with another 38% dedicated to serving infrastructure. Engineering is the primary function for these positions, with hiring concentrated in the United States and the United Kingdom. Frequent technology tags include model serving, inference infrastructure, and agent orchestration, suggesting a focus on deploying and managing AI models. In the last 30 days, Rivian has posted 4 new AI roles.
Rivian currently has 17 active AI-related roles in our index. The most common open titles are: Staff Software Engineer, ML Training and Inference Infrastructure (2), Data Annotation Specialist II, People Systems Solution Analyst, Senior Manager, Software Engineering - Enterprise Software, Senior Product Manager, Enterprise Software. Most positions are in Engineering and Product.
Rivian's active AI hiring is concentrated in: serving infrastructure (47%), agents (35%), data (12%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Rivian is hiring AI talent in: United States (15 roles), United Kingdom (1 role), Serbia (1 role).
Job postings at Rivian most frequently mention: Quantization, Autonomous Driving, Machine Learning, Real-Time Systems, Embedded Systems.
In the past 30 days, Rivian has posted 11 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Sr / Staff Machine Learning Engineer, Perception Sr/Staff ML Engineer for Rivian's Perception Team, focusing on developing, deploying, and optimizing ML models for autonomous vehicle safety-critical features. Responsibilities include owning the ML model lifecycle, architecting data pipelines, developing evaluation tools, and optimizing system performance for real-time embedded deployment. | ServeData | 9 |
| Staff ML Engineer, Hardware Software Co-Design This role focuses on optimizing quantized deep learning models for hardware acceleration in autonomous systems, bridging perception model design with efficient execution on embedded platforms. The engineer will research state-of-the-art perception models and develop optimization pipelines for quantized versions, customizing them for real-time performance and energy efficiency on next-generation autonomy hardware. | Serve | 8 |
| Sr. Staff ML Engineer, Hardware Software Co-Design This role focuses on optimizing quantized deep learning models for hardware acceleration in autonomous systems, bridging perception model design with hardware-aware deployment for embedded platforms. The engineer will research state-of-the-art perception models and develop optimization pipelines for real-time performance and energy efficiency on custom accelerators, collaborating with hardware teams for co-optimization. | Serve | 8 |
| Sr. Staff ML Engineer, Quantization & Compression This role focuses on optimizing quantized deep learning models for hardware acceleration in autonomous systems, bridging perception model design and hardware-aware deployment for embedded platforms. The engineer will research state-of-the-art perception models and develop optimization pipelines for quantized versions to achieve real-time performance and energy efficiency on custom accelerators. | Serve | 8 |
| Sr. Manager, ML Acceleration and Performance This role leads a team focused on compressing, optimizing, and deploying advanced neural networks onto Rivian's custom embedded compute platforms. The goal is to ensure the autonomy stack is performance-first while meeting next-generation safety requirements, bridging ML research with low-level silicon constraints. | Serve | 8 |
| Staff Software Engineer, ML Training and Inference Infrastructure Staff Software Engineer focused on ML training and inference infrastructure for perception systems in autonomous driving vehicles. Responsibilities include optimizing performance of deep learning training on GPUs and optimizing inference latency on onboard systems, with a focus on transformer architectures. Requires deep knowledge of PyTorch and experience with large-scale distributed training. | ServePost-train | 8 |
| Staff Software Engineer, ML Training and Inference Infrastructure Staff Software Engineer focused on optimizing ML training and inference infrastructure for large autonomous driving models on NVIDIA GPU systems, including on-board inference latency optimization and distributed training. | ServePost-train | 8 |
| Staff Machine Learning Compiler Engineer Staff Machine Learning Compiler Engineer to develop an ML Compiler for mapping Autonomy ML models to Rivian Autonomy Processor (RAP1), focusing on hardware-aware optimizations for inference performance. | Serve | 7 |