Be a strategic thought leader for AI Foundations as a whole

Lead strategic execution around ML systems and training infrastructure and deploying large models

Be as a technical leader across the broader Cruise AI and Engineering organizations to deliver production systems and mentor Engineers

Define execution processes that strive for streamlined engineering development with robust quality and excellence

Contribute broadly on the needs and strategy from data, to training, to deployment

Utilize your deep understanding of data characteristics, model architectures, optimization techniques, or other ML domain-specific challenges to perform critical analysis of modeling results

Propose ways to improve the quality of the data for the model training and evaluation, automate data collection for reproducibility.

Closely follow industry and academic developments in the SOTA for the AI life-cycle and ML Systems domain’s and adopt technology that is the best fit for Cruise’s needs.

Own technical projects from start to finish, contribute to the team’s product roadmap, and be responsible for major technical 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 risks/conflicts. Work together with partner teams and orgs 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

5+ years working on ML systems for training and deploying complex ML models by employing SOTA techniques in the area of distributed training and deployment

Experience working on the scaling challenges associated with building LLMs and/or other large foundational models.

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 collaboratively on larger teams

Startup mentality - openness to dealing with unknown unknowns and wearing many hats

Strong expertise in writing production quality code and setting standards for code quality across engineering teams

Experience in driving technical strategy and vision for engineering teams and organizations

Leadership experience for planning and execution of cross-functional initiatives and projects

In-depth understanding of software development lifecycle (SDLC) and best practices - CI/CD, coding, debugging, optimization, testing, integration and deployment

PhD in CS/CE/EE, or equivalent, in industry experience