Remote Senior Staff Machine Learning Engineer AI Foundations

June 4, 2024

Job Description

At Cruise, the AI Foundations (AIF) team is responsible for creating the critical AI infrastructure that every machine learning engineer at the company relies on. AIF aims to support the entire AI lifecycle through its ML data platform, ML training platform, and by deploying large, complex ML models to vehicle hardware under stringent real-time constraints. The mission of AIF is to ensure the highest reliability, fastest developer velocity, and lowest cost through these platforms and services.

Cruise is developing large foundational models tailored to address autonomous driving challenges. This necessitates that the ML systems and training infrastructure scale to meet the demands of these models. Deploying these large models to edge (on-vehicle) hardware is another significant challenge. In the role of Senior Staff Engineer, you will lead the vision and strategy, as well as guide the technical execution to overcome these challenges. Cruise offers a highly collaborative and dynamic work environment. In this role, you will work closely with partners on the ML teams (Autonomy) to inspire and execute a technical strategy and vision through a cross-functional team.

Responsibilities:

  • Act as a strategic thought leader for the entire AI Foundations organization.
  • Lead the strategic execution of ML systems, training infrastructure, and deploying large models.
  • Serve as a technical leader across the broader Cruise AI and Engineering organizations to deliver production systems and mentor engineers.
  • Define execution processes that promote streamlined engineering development with robust quality and excellence.
  • Contribute to the overall needs and strategy from data to training to deployment.
  • Utilize deep understanding of data characteristics, model architectures, optimization techniques, and other ML domain-specific challenges to critically analyze modeling results.
  • Propose improvements to data quality for model training and evaluation and automate data collection for reproducibility.
  • Stay updated with industry and academic advancements in AI lifecycle and ML systems and adopt the best technologies for Cruise’s needs.
  • Own technical projects from start to finish, contribute to the team’s product roadmap, and make major technical decisions and trade-offs. Participate in planning, code reviews, and design discussions.
  • Consider the impact of projects across multiple teams, manage risks/conflicts proactively, and work with partner teams to achieve cross-departmental goals.
  • Conduct technical interviews, play a key role in recruiting, and effectively onboard and mentor junior engineers and interns.

Requirements:

  • 5+ years of experience with ML systems for training and deploying complex ML models using state-of-the-art techniques in distributed training and deployment.
  • Experience with scaling challenges associated with building large language models (LLMs) and other foundational models.
  • Passion for self-driving technology and its potential impact on the world.
  • Attention to detail and a commitment to truth.
  • Proven track record of collaboratively solving complex problems in larger teams.
  • Startup mentality with a willingness to handle unknowns and multitask.
  • Strong expertise in writing production-quality code and setting standards for code quality across engineering teams.
  • Experience driving technical strategy and vision for engineering teams and organizations.
  • Leadership experience in planning and executing cross-functional initiatives and projects.
  • In-depth understanding of the software development lifecycle (SDLC) and best practices, including CI/CD, coding, debugging, optimization, testing, integration, and deployment.
  • PhD in CS/CE/EE, or equivalent industry experience.

Bonus Points:

  • Experience distilling large foundational models for production on edge devices.
  • Strong experience with GPUs and GPU-based data centers.
  • Relevant publications.

Compensation and Benefits:

The salary range for this position is $217,600 – $320,000, depending on location, job-related knowledge, skills, and experience. Additional compensation may include a bonus, long-term incentives, and benefits. This range is subject to change.

Benefits Include:

  • 401(k) plan with matching
  • Distributed team
  • Vision, dental, and medical insurance
  • Unlimited vacation and paid time off
  • 4-day workweek
  • Company retreats, coworking budget, learning budget, free gym membership, mental wellness budget, home office budget
  • Profit sharing and equity compensation
  • No whiteboard interviews, no monitoring system, no politics at work
  • Hiring for diverse age groups