Deep Learning Engineer

About the company

Hayden AI builds computer vision systems that help transit agencies and other public-sector organizations solve practical mobility and street-safety problems. Its technology supports use cases such as bus lane and bus stop enforcement, transportation optimization, and broader efforts to improve transit performance and sustainability.

Team overview

The Deep Learning team sits at the center of Hayden AI’s product offering. It develops and maintains advanced perception models that power downstream customer applications. The team works on models that run both in the cloud and on edge devices, and partners closely with the platform team to strengthen the company’s MLOps stack for scale and reliability.

Role summary

As a Deep Learning Engineer, you will help create core AI capabilities that enable Hayden AI to solve demanding customer problems. You will design, train, validate, and deploy production-grade machine learning models at scale. In this role, you will report to the Director of AI in the Perception organization and collaborate with engineering and product teams to deliver customer value. The team values depth in one of several areas, but it is not required on day one.

Areas of focus

• 3D vision systems for depth estimation and 3D structure prediction
• Video and temporal models for intent prediction
• Vision-language models, including hands-on fine-tuning experience
• Foundation models for perception
• NVIDIA edge deployment workflows and CUDA optimization for highly efficient model execution

Responsibilities

• Develop deep learning approaches to solve challenging perception problems
• Communicate ideas clearly in spoken and written form, including design documents and project plans
• Help shape roadmap priorities and planning efforts
• Partner with cross-functional teams to deliver complete end-to-end customer solutions

Requirements

• 1 to 2 years of experience building and deploying machine learning models for perception in production environments
• Strong practical experience with model design, training, and evaluation for perception tasks
• Ability to independently build ML pipelines and deploy models to cloud platforms such as AWS, GCP, or Azure
• Working knowledge of MLOps practices, including experiment tracking, model versioning, and automated workflows
• Hands-on experience with Python and PyTorch
• Strong communication skills, a self-directed mindset, and the ability to collaborate effectively
• Quick learner who can thrive in a fast-moving startup environment
• Bachelor’s or Master’s degree in Computer Science or a related field
• Preferred: experience solving perception problems in self-driving car companies

Compensation

The salary range for this role is $161,637 to $175,000 per year.

Location and schedule

This position is based in San Francisco and follows a hybrid work arrangement with at least three days per week in the office.