Job description

Who we are Aurora’s mission is to deliver the benefits of self-driving technology safely, quickly, and broadly. The Aurora Driver aurora.tech will create a new era in mobility and logistics, one that will bring a safer, more efficient, and more accessible future to everyone. At Aurora, you will tackle massively complex problems alongside other passionate, intelligent individuals, growing as an expert while expanding your knowledge. For the latest news from Aurora, visit aurora.tech aurora.tech or follow us on LinkedIn linkedin.com. WHAT WE ARE LOOKING FOR Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all. We are seeking a Software Engineer and Machine Learning practitioner to join the Perception Tracker Team at Aurora. In this role, you will play a critical part in elevating the Aurora Driver’s perception performance and support the expansion of our driverless operational domain across key routes throughout the United States. Your work will be fundamental to scaling our mission, directly contributing to the delivery of self-driving benefits safely, quickly, and broadly. IN THIS ROLE YOU WILL - Tackle end-to-end perception challenges, including tracking dynamic actors, recognizing actions and attributes, and developing deep semantic understanding of diverse traffic environments. - Research and develop state-of-the-art machine learning models to enhance perception performance in challenging, real-world scenarios, such as highway versus urban driving, long-range multi-sensor tracking, varying weather conditions, and degraded sensor conditions. - Collaborate cross-functionally to iterate on the Perception system, translating insights from on-road and simulated testing into robust, high-quality, and well-tested software solutions. - Drive the software development lifecycle from prototype to production, focusing on large-scale data analysis and the deployment of performing, production-ready solutions on the real-time Aurora Driver platform. - Contribute to architectural strategy and team collaboration, ensuring our perception systems remain scalable, efficient, and at the forefront of autonomous driving technology. - Example projects that a candidate could potentially contribute to (list not exhaustive): - Design and implement state-of-the-art object tracking algorithms. - Design algorithms to extract, leverage, and fuse complementary information from different sensors. - Design and implement state-of-the-art ML systems for object tracking and object attribute classification leveraging expertise in recursive state estimation, Hidden Markov models, structured prediction, and sequential models. - Build and improve model pipelines for large-scale and efficient model training. - Analyze failure modes and implementation/testing of solutions to address the surfaced issues REQUIRED QUALIFICATIONS - Master's degree or higher in Computer Science, Robotics, Electrical Engineering, or a related field (or Bachelor with 1+ years of relevant industry experience in software engineering). - Proficient software engineering skills in C++ and Python, with a focus on writing clean, scalable, and efficient production-quality code. - Basic knowledge in one or more focus areas: deep learning, computer vision, recursive state estimation, structured prediction, numerical optimization, and others. - Basic knowledge about 3D object tracking algorithms. - Experience with PyTorch, Tensorflow, and/or other deep learning frameworks DESIRABLE QUALIFICATIONS - Strong grasp of fundamentals: linear algebra, discrete and continuous optimization, supervised and unsupervised methods, generative and discriminative methods, and Hidden Markov Models. - Hands-on experience with VLM, foundational or world models. - Hands-on experience in CUDA or high-performance GPU programming for accelerated computing. - Experience with deploying production-grade CV/ML models within real-time computing environments. - Demonstrated experience automating ML workflows and optimizing training pipelines for efficiency. - Contributions to open source project(s) - Publication record at top-tier robotics/computer vision conferences/journals, or strong industry experience in relevant fields (robotics, computer vision, self-driving technology) - Proven ability to thrive in highly collaborative, cross-functional engineering environments. For roles based in Pittsburgh, PA: The salary range for this position is $126,000 - $201,000 per year. Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits. Working at Aurora At Aurora, we bring together extraordinarily talented and experienced people united by the strength of our values. We operate with integrity, set outrageous goals, and build a culture where we win together — all without any jerks. We believe in-person work increases collaboration, empathy, and our ability to lead effectively. As a result, Aurorans are expected to work from the office at least 3 days per week, with some roles requiring more frequent in-office presence, up to 5 days per week, based on operational needs. Our Careers page aurora.tech provides insight into what it is like to work at Aurora, and you can find all the latest updates in our Newsroom aurora.tech. Our commitment to safety At the core of everything we do is our commitment to safety. Building best-in-class self-driving technology will take time, and we believe that each employee at Aurora has a role in contributing to safety, every step of the way. Aurora expects commitment to our safety policies from every employee, and seeks candidates who take an active responsibility, can contribute to building an atmosphere of trust, and invest in the organization’s long-term success by prioritizing working safely, no matter what. Our commitment to inclusion Aurora considers candidates without regard to their race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, pregnancy status, parent or caregiver status, ancestry, political affiliation, veteran and/or military status, physical or mental disability, or any other status protected by federal or state law. Aurora considers qualified applicants with criminal histories, consistent with applicable federal, state, and local law. We are also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, you may contact us at careersiteaccommodations@aurora.tech. For California applicants, information collected and processed as part of your application and any job applications you choose to submit is subject to Aurora’s California Employment Privacy Policy.

Requirements

Must-haves

Tackle end-to-end perception challenges, including tracking dynamic actors, recognizing actions and attributes, and developing deep semantic understanding of diverse traffic environments.
Collaborate cross-functionally to iterate on the Perception system, translating insights from on-road and simulated testing into robust, high-quality, and well-tested software solutions.
Drive the software development lifecycle from prototype to production, focusing on large-scale data analysis and the deployment of performing, production-ready solutions on the real-time Aurora Driver platform.
Contribute to architectural strategy and team collaboration, ensuring our perception systems remain scalable, efficient, and at the forefront of autonomous driving technology.
Example projects that a candidate could potentially contribute to (list not exhaustive):
Design and implement state-of-the-art object tracking algorithms.
Design algorithms to extract, leverage, and fuse complementary information from different sensors.
Build and improve model pipelines for large-scale and efficient model training.
Analyze failure modes and implementation/testing of solutions to address the surfaced issues
Master's degree or higher in Computer Science, Robotics, Electrical Engineering, or a related field (or Bachelor with 1+ years of relevant industry experience in software engineering).
Proficient software engineering skills in C++ and Python, with a focus on writing clean, scalable, and efficient production-quality code.
Basic knowledge in one or more focus areas: deep learning, computer vision, recursive state estimation, structured prediction, numerical optimization, and others.
Basic knowledge about 3D object tracking algorithms.
Experience with PyTorch, Tensorflow, and/or other deep learning frameworks
Strong grasp of fundamentals: linear algebra, discrete and continuous optimization, supervised and unsupervised methods, generative and discriminative methods, and Hidden Markov Models.
Hands-on experience with VLM, foundational or world models.
Hands-on experience in CUDA or high-performance GPU programming for accelerated computing.
Experience with deploying production-grade CV/ML models within real-time computing environments.
Demonstrated experience automating ML workflows and optimizing training pipelines for efficiency.
Contributions to open source project(s)
Publication record at top-tier robotics/computer vision conferences/journals, or strong industry experience in relevant fields (robotics, computer vision, self-driving technology)
Proven ability to thrive in highly collaborative, cross-functional engineering environments.
Working at Aurora
Our Careers page https://aurora.tech/careers provides insight into what it is like to work at Aurora, and you can find all the latest updates in our Newsroom https://aurora.tech/newsroom.

Nice-to-haves

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Application prep

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Keywords to mirror

gomachine learningmlpython

Platform: ashby
Effort: quick

Benefits

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