Systems Engineer, Autonomy Software

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

Who We Are

Nuro is a robotics start-up whose mission is to accelerate the benefits of robotics for everyday life. We have an elite team of entrepreneurs and engineers, designers, and scientists. We believe AI and robotics are at the cusp of transforming daily life and we are dedicated to building meaningful products with this technology. Join us and play a critical role in our mission.

About The Team

The Systems Engineering team is responsible for the requirements, architecture, and validation of autonomous driving capabilities across engineering disciplines. This includes designing performance metrics, evaluation methods, and criteria for success, which the team then drives cross-functional via requirement definition and system validation. Systems Engineering works at the intersection of hardware, software, and robot operations, with a deep understanding of technologies in all three. We are a small, high-impact team that sets the checkpoints for autonomy deployment.

About The Role

As a Systems Engineer - Autonomy you will work very closely with the software engineering, autonomy product, and data science teams to build scalable validation methodology and tools for assessing autonomy functionality. As a key part of Nuro's system validation approach, you will help create technologies that will drive autonomy development and gate the readiness of our robots on public roads. Your work is expected to have short term impact in our next deployments, as well as long term impact on autonomy feature roadmapping and Nuro’s scaled fleet operations.

About Your Work

• Dive into the system-level implications of Nuro’s autonomy architecture and software, and drive validation concepts from prototype to production to test
• Work closely with autonomy developers to extract high-impact metrics and performance indicators that will test our robots’ readiness to drive autonomously on public roads
• Support software development for automating data log processing from onroad tests and closed course tests, and support simulation tools to scale testing across variations of environment and agent behavior
• Support the development of tools and data engineering frameworks that can interpret results from curated amounts of simulation, onroad, closed course testing to assess mission capabilities and safety
• Design experiments and perform trades studies to assess performance, safety, risk, and cost of competing technical solutions at the system or subsystem level

About You

• Bachelor’s Degree or Master’s Degree candidate in Computer Science, Math, Electrical Engineering, Mechanical Engineering, Robotics, Physics, or related field
• Strong programming and algorithmic problem solving skills. You do not need to know data structures, but should be able to script prototypes and review code easily.
• Technically fluent and experience working in a team with strong software engineering practices
• Deep understanding of how robotic systems work and ability to leverage this knowledge to build tooling and infrastructure to evaluate them 
• Highly collaborative in nature with strong abilities to think and communicate analytically and effectively
• Self starter and fast learner - you should be passionate about picking up new skills and approaching unstructured problems from first principles
• You must have at least 7 years of experience in one or a combinationof the following (not necessarily in industry):
  • Designing statistical inference methods for data produced from various experiments on physical systems
  • Software development and QA in one or more of autonomy’s core modules: localization, perception prediction, planning, controls
  • Analyzing and managing FDIR (fault detection, isolation, recovery) for the software stack on semi-autonomous or autonomous vehicles or equipment 
  • Implementation of the V model of systems engineering on a delivered product in the capacity of management of at least one of: architecture, requirements, configuration, or interfaces
  • End-to-end functional decomposition, defining physical/logical architectures, allocating functionality, and reliability analysis of safety-critical complex systems
  • End-to-end parametric characterization of human road user behavior and ODDs, which quantitatively informs scenario generation and simulation realism assessment 
  • Man-machine interface design, development, and validation testing for teleoperations of vehicles (aerial or terrestrial) in safety-critical environments