Senior Software Engineer II, ML Orchestration

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 ’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 Machine Learning Orchestration team owns and develops Cruise’s workflow management platform. The platform provides a semantic orchestration framework for machine learning workflows and data processing  provide the necessary orchestration, big data, and compute layer to greatly accelerate the development cycle of AV engineers by empowering engineers to focus on improving the car’s safety and performance.

We are seeking an experienced Senior Software Engineer to lead key initiatives within our ML Orchestration team, focused on helping scale our platform, create automation and self‑service tools for our users, and help us run ML pipelines efficiently  successful candidate will have experience building and running scalable distributed systems, an understanding of open‑source orchestration platforms such as Air Flow / Kube Flow / Meta Flow / Flyte, will bring innovative ideas and approaches, and should have intellectual curiosity and strong problem‑solving skills.

Note:

This role is for an AI/ML infrastructure engineering team, not an applied machine learning team. This team does not build ML models for specific applications. The team is focused on the infrastructure products that help our customers do machine learning and data science erience with ML or data platforms is helpful to understand our customer use cases, but your team will not do any applied ML.

• Use the latest cloud (GCP/Azure) technologies to own, design, implement, and test scalable distributed compute and data processing in the cloud. Champion engineering excellence by continuously improving systems and processes.
• Own technical projects from start to finish, and be responsible for major technical design decisions and tradeoffs.
• Effectively participate in team’s planning, code reviews, and design discussions.
• Consider the effects of projects across multiple teams and proactively manage conflicts. Work together with partner teams to achieve cross‑departmental goals and satisfy broad requirements.
• Conduct technical interviews with well‑calibrated standards and play an essential role in recruiting activities. Effectively onboard and mentor junior engineers and/or interns.

• 7+ years experience, with work on large‑scale distributed systems preferred.
• 3+ years of experience leading and driving complex projects.
• Experience building scalable infrastructure on the cloud with Python, C++, or Golang (or similar).
• Experience working with relational and No
  
  SQL databases.
• Experience developing and maintaining systems at scale.
• BS, MS, or Ph.D. in Computer Science, Electrical Engineering, Mathematics, Physics, or another relevant field; or equivalent real‑world experience.
• Passionate about self‑driving technology and its potential impact on the world.
• Attention to detail and a passion for truth.
• A track record of efficiently solving complex problems.
• Startup mentality – openness to dealing with unknown unknowns and wearing many hats.

• Experience with Google Cloud Platform, Microsoft Azure, or Amazon Web Services.
• Experience with open-source orchestration platforms such as Kubeflow, Flyte, Airflow, Metaflow, Prefect, Cadence, etc.
• Experience with Kubernetes.
• Understanding of Machine Learning (ML)…