Senior Research Engineer, Controls

Plus 2; Santa Clara (CA); On-site; USD 100,000 - 140,000; Full time

Benefits offered by this job

Catered free lunch

Unlimited snacks and beverages

Competitive salary and benefits package

Job summary

Plus 2 is seeking a Research Engineer to drive the future of autonomy in Santa Clara, California. You will be integral to delivering advancements in AI-based virtual driver software, enhancing control algorithms, and testing vehicles in real-world conditions.

Ideal candidates hold a Master's or PhD and have robust experience in robotics and motion control. Plus 2 offers a competitive salary, extensive benefits including a 401(k), and an opportunity to work in an innovative environment.

Qualifications

• 2+ years of experience in machine learning or robotics applications.
• Strong foundation in motion control and artificial intelligence.
• Hands-on experience with data processing pipelines.

Responsibilities

• Design and enhance control algorithms integrating MPC and learning-based approaches.
• Develop dataset generation and evaluation tools for online control optimization.
• Lead vehicle testing planning and execution.

Skills

Motion control

Machine Learning Engineering

Python

C++

Robotics

Education

Master's or PhD in Computer Science/Mechanical Engineering/Robotics/Aerospace Engineering

Tools

PyTorch

Linux

Job description

PlusAI is a Physical AI company pioneering AI-based virtual driver software for factory-built autonomous trucks. Headquartered in Silicon Valley with operations in the United States and Europe, Plus was named by Fast Company as one of the World’s Most Innovative Companies. Partners including TRATON GROUP’s Scania, MAN, and International brands, Hyundai Motor Company, Iveco Group, Bosch, and DSV are working with Plus to accelerate the deployment of next‑generation autonomous trucks. If you’re ready to make a huge impact and drive the future of autonomy, Plus is looking for talented individuals to join its fast‑growing teams.

As a Research Engineer, you will deliver mission‑critical improvements and new features for our autonomy motion planning and control stack. You will be a crucial part of our team, working alongside engineers, research scientists, and domain experts to build optimal and data‑driven controls to realize planned vehicle trajectories.

Your responsibilities will include the development of machine‑learning vehicle models and learning‑based control policies leveraging the extensive data we collect every day across our autonomous trucking fleet. You will also have the opportunity to solve real‑world autonomy system challenges by participating in vehicle performance analysis, tuning, and troubleshooting. You will contribute significantly to our commitment to pushing the frontiers of technological innovation in Autonomy.

Key Responsibilities

• Design, implement, and enhance control algorithms by developing frameworks that integrate MPC with learning based approaches (DL/RL/IL)
• Work cross-functionally with domain experts to implement data driven controller design for scalability
• Develop tools and infrastructure for dataset generation, training, and evaluation to drive advancements in online control optimization
• Ensure all model development keeps a real-time focus and operates efficiently in compute-constrained environments
• Take a lead role in the planning and execution of vehicle testing in the offline simulation environment and on the public road to systematically improve performance, as well as performing root cause analysis and debugging to address the issues
• Track and incorporate the latest research advancements

Qualifications

• Master's or PhD degree in Computer Science, Mechanical Engineering, Robotics, Aerospace Engineering or related field
• 2+ years of MLE experience or industry experience designing and developing for robotics applications
• Strong foundation in motion control and modern neural network architectures, with expertise in at least one application area, such as IL/RL, time-series analysis, or dynamic system modeling
• Skilled in debugging robotic systems within Linux environments, with strong programming expertise in Python and C++
• Experience model development & training with modern frameworks (e.g. PyTorch)
• Hands‑on familiarity with data ingestion and processing pipelines
• Hands‑on application skills in any of the following areas: adaptive and nonlinear control, MPC & optimal control, robust control, data-driven control, Kalman filters, etc.
• Have a solid understanding of AV control, vehicle dynamics and drive-by-wire systems
• Proven expertise with application, verification and validation for ADAS/autonomous driving features and functions

Opportunities

• Work, learn and grow in a highly future-oriented, innovative and dynamic field.
• Wide range of opportunities for personal and professional development.
• Catered free lunch, unlimited snacks and beverages.
• Highly competitive salary and benefits package, including 401(k) plan.