Helm.ai

Develop productionized ML workflows and platform infrastructure for training, validating, and deploying neural networks. Build distributed data-processing pipelines, internal APIs, and CI/CD processes to enhance developer productivity.

Collaborate on improving AI models and iterating on novel research directions for unsupervised learning and perception. Develop and maintain deep learning tools and deploy algorithms onto internal and customer autonomous vehicle platforms.

Collaborate on improving AI models and iterating on novel research directions for unsupervised learning and perception. Develop and maintain deep learning tools and deploy algorithms onto internal and customer autonomous vehicle platforms.

Design and implement safe, scalable real-time software for mass-production autonomous vehicle systems. Collaborate with AI teams and vendors to optimize the AV stack and architect continuous learning systems for ML models.

Architect and design scalable ML infrastructure and services to handle large-scale training and massive datasets. Lead the end-to-end platform lifecycle while mentoring engineers and collaborating with cross-functional teams.

The engineer will collaborate with researchers to execute research operations using existing infrastructure, focusing on characterizing neural network quality, failure modes, and edge cases based on research data. Key tasks include managing concurrent experiments, reviewing results, suggesting improvements, and writing technical reports detailing qualitative and quantitative outcomes.