Senior Machine Learning Engineer, Simulation

Plus; Santa Clara (CA); On-site; USD 125,000 - 150,000; Full time

Job summary

An innovative company is looking for a Senior Machine Learning Engineer to revolutionize vehicle simulation models. In this exciting role, you will leverage deep learning and data analysis to create high-fidelity models that enhance autonomous driving technology. Collaborating with diverse teams, you'll develop scalable vehicle dynamics models and integrate them into simulation pipelines, driving innovation in the field. If you're passionate about advancing technology in autonomous vehicles and have a strong background in machine learning, this is the perfect opportunity to make a significant impact in a forward-thinking environment.

Qualifications

• 5+ years experience with MS or 2+ years with PhD in relevant fields.
• Proficient in Python and C++ for large codebases.

Responsibilities

• Develop scalable vehicle dynamics models using deep learning techniques.
• Conduct analysis of road test data to enhance model accuracy.
• Integrate models into simulation pipelines for compatibility.

Skills

Deep Learning

Data Analysis

Vehicle Dynamics Modeling

Python

C++

Communication Skills

Education

MS in Mechanical Engineering

PhD in Computer Science

BS in Related Field

Job description

We are seeking a Senior Machine Learning Engineer with expertise in deep learning, data analysis, and vehicle dynamics modeling. 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.

Required Skills

• MS (with 5+ years of relevant experience) or PhD (with 2+ years) 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.
• Strong understanding of conventional vehicle dynamics modeling.
• Proficient in Python and C++, with experience working in large codebases.
• Excellent communication skills and the ability to collaborate effectively in a team setting.

Preferred Skills

• Familiarity with state-of-the-art deep learning models and their applications.
• Experience with autonomous vehicle or robotics simulation and related concepts.
• Background in autonomous vehicle prediction, planning, and control.