What We’re Looking For:

We are seeking passionate individuals to join our team, driven to develop and deploy advanced AI products that redefine industry standards, making processes safer, faster, and more efficient. If you thrive in fast-paced tech environments and are eager to contribute to transformative AI solutions, we invite you to join us in shaping the future of technology.

About the Team:

The ML Platform org at Stack AV develops the platform that powers all AI at Stack, including data collection, model training, testing, and deployment on the autonomous vehicles. The ML Developer Velocity team is responsible for the overall velocity of ML engineers, building the tools to enable development of all the AI applications that make autonomous vehicles a reality as safely and as efficiently as possible. The scope for this team includes building tools for experiment management, model testing & safety validation, and training data influence analysis.

Position Overview:

We are seeking an experienced and hands-on engineer for our ML Developer Velocity team. The ideal candidate has a strong infrastructure and machine learning background, with some previous experience either as an ML Engineer or having worked closely with ML Engineers.

Team Responsibilities:

• Work regularly with ML Engineers to understand their development workflow and improve it. This includes understanding the overall flow of going from on-road improvement requirements to having a deployed model on the truck and improving the workflow.
• Automation of manual work is a large part of this job. Examples include converting manual work to automated pipelines (on Flyte) and  creating metrics that can make automated go/no-go decisions on model deployment.
• Experiment management using third-part tools (like MLFlow) and connecting this to the rest of development workflow (data infra and training infra).
• Work with open source teams to merge our changes upstream.

Key Responsibilities:

The successful candidate will have a significant impact on what models can be deployed on the AV hardware as well as the development experience and velocity of ML engineers across the company.

• Understand the needs and pain points of ML Engineers across the company and develop solutions to improve the overall velocity and user experience.
• Propose solutions using a mixture of front end and backend changes to meet our customer needs.
• Collaboration: Collaborate with cross-functional teams to understand data requirements and design appropriate solutions.
• Technology Stack: Stay updated with the latest technologies and trends in ML. 
• Promote Engineering Excellence: Set a culture of engineering excellence within the team and work closely with the management and customer teams to balance between speed of delivery and quality of engineering artifacts.

Qualifications:

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Experience: 5+ years of experience in ML Infra / MLE. Familiarity with infra / front end ideal.
• Technical Skills:
  • Strong programming skills in Python.
  • Strong service system design skills.
  • Comfortable driving designs across multiple groups to unblock a project.
  • Familiar with ML Engineer user journeys and comfortable working closely with ML Engineers.
  • Comfortable working on all parts of the stack, front end, backend, generic infra, and ML infra.
  • (preferred) prior experience with offline ML pipelines and experiment management tooling. In particular, Flyte, MLFlow and Weights and Biases.
• Problem-Solving: Strong analytical and problem-solving skills.
• Communication: Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders. #LI-AW1