Senior Full-Stack Software Engineer, Machine Learning Labeling

We're Cruise, a self-driving service designed for the cities we love.

We’re building the world’s most advanced self-driving vehicles to safely connect people to the places, things, and experiences they care about. We believe self-driving vehicles will help save lives, reshape cities, give back time in transit, and restore freedom of movement for many.

In our cars, you’re free to be yourself. It’s the same here at Cruise. We’re creating a culture that values the experiences and contributions of all of the unique individuals who collectively make up Cruise, so that every employee can do their best work. 

Cruise is committed to building a diverse, equitable, and inclusive environment, both in our workplace and in our products. If you are looking to play a part in making a positive impact in the world by advancing the revolutionary work of self-driving cars, come join us. Even if you might not meet every requirement, we strongly encourage you to apply. You might just be the right candidate for us.

The ML Data Shop team is responsible for building the data platform for Cruise AI, where we build the platform to efficiently generate data, search for long tail and impactful on-road scenarios, and provide ground truth for model training and testing to improve our autonomous vehicles. Our platform needs to provide high quality data on time with low cost and reliably scale to serve the petabyte-scale data requirements.

We're looking for a Senior Full-Stack Software Engineer with ML infrastructure and ML data experience to design and implement platforms that support data labeling to accelerate the AV model development.

What you’ll be doing: 

• Use the latest ML infrastructure and web technologies to design, implement, and test scalable and performant data systems and user interfaces. Champion engineering excellence by continuously improving systems and processes.

• Build automation that surfaces insights on how machine learning engineers can improve workflow efficiency. 

• Work closely with machine learning engineers to enable cutting-edge R&D efforts and improve existing systems.

• Own technical projects from start to finish. Effectively participate in team’s planning, code reviews and design discussions

• Work together with partner teams and orgs to achieve cross-departmental goals and satisfy broad requirements

 

What we are looking for: 

• BS, MS or Ph.D. in Computer Science, Electrical Engineering, Mathematics, Physics, or another relevant field; or equivalent real-world experience.

• 4+ years experience working on both front and back ends for ML infrastructure systems (ML data labeling systems, ML data pipelines, ML model training frameworks etc.).

• At least one of the following:

  • Front end experience writing high quality, scalable and performant code in TypeScript, React, Redux, WebGL (or similar), and working with web interfaces using large amounts of data using Service Workers, Cache Storage, IndexedDB (or similar)

  • ML Experience working on computer vision, machine learning or related projects from ideation to completion, with hands-on experience performing ML model fine-tuning, inference and performance evaluation.

• Experience writing production quality code in Golang or Python (or similar) 

• Experience working with A/B testing frameworks and telemetry systems

• Strong computer science fundamentals in object oriented programming, scalable software systems, data structures, algorithm design, best practices, and complexity analysis.

• Strong understanding of relational databases, data modeling, and API definition.

• Passion for self-driving technology and its impact

• Drive for learning new technologies and expanding technical skill set

• Experience and proficiency shipping products end-to-end

• Technical communication/collaboration skills: technical writing

• Demonstrated ability to empathize with customer problems and deliver creative product solutions

 

Bonus points!

• Strongly preferred: Experience working on data labeling for ML or other projects using data centric AI, active learning techniques.

• Experience with autonomous vehicle technology.

• Experience building tools that are core to a machine learning engineer’s daily work

• Experience building data visualization products using libraries such as three.js, d3, WebGL.

• Experience with large-scale distributed storage a