Machine Learning Engineer Quantization Jobs in Blacksburg, VA

About the Company At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business. A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family , we are focused solely on developing software for automated trucks to transform how the world moves freight. Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.

Torc's Multi-Modal Perception team is responsible for developing the machine learning systems that enable our autonomous trucks to perceive and understand the world around them. By combining information from cameras, LiDAR, and other sensor modalities, the team builds production-ready perception capabilities that provide the foundation for safe, reliable autonomous driving.

Design, develop, and improve machine learning models supporting Torc's perception systems. Own model development and delivery for well-defined perception problem areas, from data preparation and training through evaluation and integration. Write production-quality Python and PyTorch code to support scalable training, evaluation, and inference workflows. Analyze model performance, identify failure modes, and independently troubleshoot issues to improve robustness, accuracy, and generalization. Develop and evaluate perception models leveraging multi-modal sensor data, with an emphasis on camera-based and 3D perception systems. Collaborate with software engineers, infrastructure teams, and autonomy engineers to integrate perception models into larger production software systems. Contribute to improvements in training pipelines, data workflows, experimentation tooling, and developer workflows that accelerate model iteration and deployment. Participate in model architecture discussions and contribute technical recommendations within the team. Lead small technical initiatives or model components with guidance from senior engineers. Support and mentor Machine Learning Engineer I team members on implementation, experimentation, and machine learning best practices. Document technical work, evaluation results, and design decisions to support knowledge sharing and long-term maintainability.

Bachelor's degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field with 3+ years of relevant industry experience, OR Master's degree with 1+ years of relevant experience, or equivalent practical experience. Experience developing machine learning models for computer vision, perception, robotics, autonomous systems, or a closely related domain. Strong programming skills in Python and PyTorch, with experience writing maintainable, production-quality machine learning code. Experience training, evaluating, and improving deep learning models using large-scale datasets. Experience working with image-based and/or 3D perception systems. Solid understanding of deep learning architectures commonly used for perception applications. Experience debugging model behavior, analyzing performance metrics, and proposing practical improvements. Ability to independently execute complex machine learning work within well-defined problem areas. Experience collaborating cross-functionally to integrate machine learning models into larger software systems. Strong problem-solving skills with the ability to operate effectively in an environment with evolving technical challenges and requirements. Bonus Points Experience developing perception systems for autonomous driving, robotics, or ADAS. Experience with LiDAR, point cloud processing, sensor fusion, BEV representations, or other 3D perception techniques. Experience with temporal perception models or video-based learning. Experience with C++, ROS, or robotics software development. Experience deploying machine learning models into production autonomy or robotics platforms. Experience working with large-scale perception datasets and distributed training environments. Familiarity with perception evaluation frameworks, model validation, and performance benchmarking. Experience improving ML tooling, automation, training workflows, or experimentation infrastructure. Experience leading a small technical initiative or owning a production ML component from development through deployment.

For this position, we are open to hiring in Ann Arbor, MI, Blacksburg, VA, Fort Worth, TX office work locations in a hybrid capacity. We are also open to hiring Remote in the United States.

• A competitive compensation package that includes a bonus component and stock options
• 100% paid medical, dental, and vision premiums for full-time employees
• 401K plan with a 6% employer match
• Flexibility in schedule and generous paid vacation (available immediately after start date)
• Company-wide holiday office closures AD+D and Life Insurance

At Torc, we’re committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc’rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities.

Even if you don’t meet 100% of the qualifications listed for this opportunity, we encourage you to apply. Our compensation reflects the cost of labor across several geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Torc's total compensation package will also include our corporate bonus and stock option plan. Dependent on the position offered, sign-on payments, relocation, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.

Job ID: 102882 Hiring Range for Job Opening US Pay Range $153,200 — $183,800 USD