Simulator Realism Software Engineer (Senior/Staff)

Tensor is an agentic AI company dedicated to building agentic products that empower individual consumers. Our flagship product, the Tensor Robocar, is the world’s first personal Robocar and the first AI agentic vehicle — fully autonomous, automotive-grade, and built for private ownership at scale. Founded in 2016 in Silicon Valley, Tensor is headquartered in San Jose, California, with offices in Barcelona, Singapore, and Dubai. At Tensor, we champion personal AI autonomy and ownership. Our vision is to build a future where everyone owns their own Artificial General Intelligence — a personal AGI that enables more time, freedom, and autonomy. We’re forging an alternative path where AGI serves only you, and is controlled solely by you.

We provide a competitive compensation package, opportunities for professional growth, participation in a discretionary equity incentive plan, and access to a comprehensive company benefits program, subject to eligibility requirements.

Join us to shape the future! Work with brilliant minds on technology transforming automotive industry and make a lasting impact.

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The Offboard Discovery & Realism org builds state of the art simulations of realistic environments for training of autonomous vehicle. We use machine learning to model the real world, including realistic agents (vehicles, pedestrians, cyclists, motorcyclists), roads, traffic control systems, and weather. To guide the development of simulator realism components, we create metrics to measure realism, which are used to assess the quality of the simulator, identify sim2real gaps, and used as loss functions to train a more realistic simulator - which in turn is used to assess the quality of Tensor autonomous vehicle driver.

Locations

• San Jose, California, US (Salary Range: $75k—$300k USD)
  
  

Responsibilities

• Improve software architecture of close-loop simulator to eliminate known realism gaps
• Develop fault injection framework to inject problematic sensor data and perception output, and inject failures of software modules
• Improve hardware-in-loop simulation realism
• Develop novel methods to measure sim realism in the context of several simulator tech and applications
• Develop systems that can automatically discover useful realism metrics to guide simulator development
• Collaborate with machine learning engineers and data scientists to use ML models to improve simulator and sim agents realism to power the evaluation of Tensor autonomous vehicle driver
  
  

Qualifications

• Master degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• 3 years experiences working on robotics or simulation
• 3 years experiences working on large scale software products and using advanced design patterns
• Strong modern C coding skills and system design skills
• Excellent communication, strong analytical thinking and problem-solving skills
• Experience in mentoring/influencing junior engineers
  
  

Preferences

• 3 years experiences navigating a complex product space and setting technical roadmaps
• Experience leading cross-functional collaborations
  
  

We appreciate your interest in joining Tensor. Tensor is an equal employment opportunity employer, dedicated to fostering a respectful, supportive, and inclusive workplace for all. We do not discriminate against, and strictly prohibit harassment of, any applicant or employee on the basis of race, color, sex, sexual orientation, gender identity or expression, religion, national origin, age, disability, military or veteran status, genetic information, or any other characteristic protected by applicable law. Tensor also considers qualified applicants with criminal histories in accordance with applicable laws. We are committed to providing equal opportunities for qualified individuals with disabilities. Tensor is an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.