About the Role:In the ML Training, our mission is to provide a reliable, scalable, and easy to use training framework for modeling needs of Stack AV. In addition, this team is responsible for the overall developer experience of ML engineers including building tools for testing, validation, and understanding models and the data used to train them. Finally, we are responsible for model optimization and deployment.
Responsibilities: - Experience with both ML Platforms and building ML-based applications.
- Experience building scalable, reliable infra at a fast-paced environment working with MLEs on several different modeling teams.
- A deep understanding of design tradeoffs and ability to articulate those tradeoffs and work with others on getting alignment.
- Experience with building ML models or ML infra in the domains of autonomous vehicles, perception, and decision making (desirable but not required).
- Experience with model training, model optimization, or large data processing pipelines.
Qualifications (Preferred): - Built an end to end ML model pipeline including components such as logs processing, feature extraction, dataset storage, model configuration management, model training, experiment frameworks, and serving deployment.
- Shipped ML products (NLP, computer vision, recommender systems, etc.) at scale to make business impact.
- Knows how to build appropriate abstractions and tooling to ensure MLEs are able to rapidly iterate on models.
- Prior AV experience
