Staff Deep Learning Engineer
Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on Jul 17, 2026. Hayden AI scores B on the Alion truth index.
About Us
At Hayden AI, we are on a mission to harness the power of computer vision to transform the way transit systems and other government agencies address real-world challenges.
From bus lane and bus stop enforcement to transportation optimization technologies and beyond, our innovative mobile perception system empowers our clients to accelerate transit, enhance street safety, and drive toward a sustainable future.
About the Role
As a Staff Deep Learning Engineer in the Deep Learning team at Hayden, you are a technical anchor for the team - able to own and deliver complex, long-horizon perception projects while elevating the engineers around you. You bring mastery in at least two of the verticals below and broad proficiency across the full ML stack: model design, training, optimization, MLOps, and cloud/edge deployment. Beyond individual execution, you help shape the team's technical direction, mentor engineers, and drive alignment with cross-functional partners.
We’re looking for someone who enjoys being challenged with complex problems in perception and loves working with a bunch of smart people applying state of the art techniques in deep learning to provide impactful solutions to problems faced by Hayden AI’s customers
Key Responsibilities
Below are your primary responsibilities. These represent the core areas where you’ll make an impact. As part of a rapidly evolving team, we look forward to your impact expanding over time.
Lead end-to-end delivery of large-scope perception projects, from design through production
Define and document technical approaches; drive alignment across Deep Learning, Platform, and Product teams
Mentor junior and mid-level engineers through code review, design feedback, and hands-on pairing
Contribute to team roadmap and help evaluate and prioritize new technical investments
Set and uphold engineering quality standards across model development, MLOps, and deployment
Ability to work on abstract and ambiguous problems with different stakeholders like Product and program management and delivering high quality solutions in a timely manner.
Required Qualifications
The qualifications below outline the experience and skills most relevant to success in this role. We recognize that skills and potential come in many forms, and we welcome diverse experiences that advance our mission.
Education: Bachelor's degree in Computer Science, Robotics, Computer Vision, Electrical Engineering, or a related field
Experience: 8+ years building and deploying ML models in production; prior experience in a tech lead or staff-equivalent role preferred
Depth: Mastery in at least 2 of the below perception verticals:
3D vision models to predict depth and 3D structure.
Video/temporal behavior models to predict intent.
Vision language models and hands-on experience fine tuning them.
Foundation models in perception.
Nvidia edge device stack for running ML models and cuda know-how in terms delivering highly optimized models.
Breadth: Working proficiency across model training, evaluation, optimization, cloud and edge deployment, and MLOps (pipelines, experiment tracking, CI/CD for ML)
Leadership: Proven ability to mentor engineers, lead technical discussions, and influence cross-team decisions
Personal Attributes: Excellent written and verbal communication skills, able to write clear design docs and project plans; thrives in a fast-paced startup