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# Senior Machine Learning Engineer, Simulation in Santa Clara

- **Company:** Energy Jobline
- **Location:** Santa Clara, CA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Data Analysis, C++ (Programming Language), Python (Programming Language), Machine Learning, Test Data, Deep Learning, Information Technology, Data Analytics, Codebase
- **Published:** October 2, 2026
- **Apply:** https://www.energyjobline.com/job/senior-machine-learning-engineer-simulation-santa-clara-31761072

## About the Role

* MS (with 3+ years of relevant experience) or PhD new grad in mechanical, electrical, aerospace engineering, physics, computer science, or a related field.
 * Extensive experience applying deep learning techniques to time series forecasting and data analysis.
 * Proficient in Python with experience working in large codebases.
 * Excellent communication skills and the ability to collaborate effectively in a team setting.
 * Familiarity with state-of-the-art deep learning models and their applications.
 * Ensure that technical work meets customer requirements, regulatory standards, and company quality policies.

Skills

 * Proficient in C++
 * Background in autonomous vehicle prediction, planning, and control
 * Strong understanding of conventional vehicle dynamics modeling
 * Experience with autonomous vehicle or robotics simulation and related concepts

## Description

We are seeking a Senior Machine Learning Engineer with expertise in deep learning and data analysis. In this role, you will apply data-driven techniques to develop high-fidelity, scalable vehicle simulation models tailored to various vehicle platforms. You will collaborate with cross-functional teams to advance autonomous driving technology and drive innovation in simulation and model development. Responsibilities:

 * Develop accurate, scalable vehicle dynamics models from collected road test data, leveraging deep learning and advanced data analysis techniques.
 * Conduct in-depth analysis of road test data to identify trends, anomalies, and key performance indicators to enhance model accuracy.
 * Integrate the data-driven models into simulation pipelines with seamless compatibility.
 * Design and implement an automated modeling pipeline for periodic model training, evaluation, and updates.
 * Collaborate with cross-disciplinary teams to reproduce and resolve issues encountered during real-world road tests.
 * Ensure that technical work meets customer requirements, regulatory standards, and company quality policies.
 * Ensure that your work is performed in accordance with the company's Quality Management System (QMS) requirements and contribute to continuous improvement efforts.