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# Staff Machine Learning Engineer, Software Vehicle Controls

- **Company:** Rivian
- **Location:** Palo Alto, CA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Dynamical Systems, Python (Programming Language), Machine Learning, Reinforcement Learning, Apache Spark, Deep Learning, Information Technology, Machine Learning Operations, Recurrent Neural Networks
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25303_15647ff01d603a0b6dc07071fef5d8fe-1859816213

## About the Role

* S. or Ph.D. in Machine Learning, Engineering, Computer Science, or related STEM disciplines.
 * 5+ years of industry experience in ML systems.
 * Expert-level proficiency in Python and Apache Spark.
 * In-depth understanding of statistical and machine learning concepts, including deep and reinforcement learning.
 * Strong knowledge in mathematical modeling, RNNs, CNNs, Transformers, LSTMs, reinforcement learning, imitation learning, GANs, and time-series analysis and modeling of dynamic systems.
 * Understanding electric vehicle controls and propulsion, encompassing high-voltage batteries, energy management, charging, or vehicle suspension.
 * Excellent communication and interpersonal skills for both technical and non-technical audiences.
 * Outstanding team player, capable of building consensus in a dynamic environment.
 * Proven ability to provide direction, guidance, and hands-on support to drive results.

## Description

* As a member of the Vehicle Controls team, you will design, implement, and optimize deep learning dataset generation, training, and evaluation tools and infrastructure to advance the state of the art in vehicle online optimizations.
 * Develop domain-specific digital twins in collaboration with vehicle controls SW engineers to mimic and adapt electric vehicles' overall performance.
 * Develop statistical and machine learning models for estimating trip energy consumption, charging behavior, battery aging, and remaining useful life.
 * Ship and deploy ML models for various vehicle domains to enhance electric vehicles' efficiency across different operating conditions.
 * Work cross-functionally with domain experts and other data stakeholders to specify, implement, and deliver meaningful insights for electric vehicle controls and propulsion.
 * Foster collaboration among engineering peers by creating well-structured, adaptable designs and code that promote teamwork and practical solutions.
 * Demonstrate your ability to facilitate consensus during complex technical discussions, ensuring that we maintain a productive and cooperative working environment.
 * Build deep learning models to enhance vehicle calibrations throughout its lifetime.