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Evening Computer Vision Deep Learning Engineer Jobs

Hayden AI

Deep Learning Engineer

San Francisco, CA · On-site

$161K - $175K/yr

About Us At Hayden AI, we are on a mission to harness the power of computer vision to transform the ... About the Role As a Deep Learning Engineer at Hayden, you will make key contributions towards ...

NBCUniversal

Senior Deep Learning Engineer

$107K - $146K/yr

They are seeking a Senior Deep Learning Engineer to implement core algorithms at the intersection ... Responsibilities : • Implement core deep-learning, computer vision, and (inverse-)procedural ...

NBCUniversal

Staff Deep Learning Engineer

They are seeking a Deep Learning Engineer to implement core algorithms at the intersection of computer vision and computer graphics, focusing on manipulating large 2D and 3D media datasets.

Duranta

Computer Vision Engineer

Seattle, WA · On-site

$126K - $149K/yr

They are seeking a Senior Computer Vision Engineer to contribute to the development of computer ... Required : • 5+ years experience in ML / deep learning, ideally in Computer Vision • Strong ...

Zensors

AI/ML Infrastructure Engineer

San Francisco, CA · On-site

$126K - $166K/yr

As a Machine Learning Engineer in ML Runtime & Optimization , you will develop technologies to ... Work in Computer Vision , Deep Learning, and Vision Transformers. * Experience with video ...

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Evening Computer Vision Deep Learning Engineer information

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$48.5K

$121.5K

$137.5K

How much do evening computer vision deep learning engineer jobs pay per year?

As of Jul 1, 2026, the average yearly pay for evening computer vision deep learning engineer in the United States is $121,515.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,500.00 and $131,500.00 per year, depending on experience, location, and employer.

What is the difference between Evening Computer Vision Deep Learning Engineer vs Computer Vision Deep Learning Engineer?

AspectEvening Computer Vision Deep Learning EngineerComputer Vision Deep Learning Engineer
Required CredentialsBachelor's or Master's in CS, AI, or related fields; experience with deep learning frameworksBachelor's or Master's in CS, AI, or related fields; experience with deep learning frameworks
Work EnvironmentTypically evening or night shifts, often in research labs or tech companiesStandard daytime hours, in offices or remote settings
Industry UsageUsed in industries with 24/7 operations like surveillance, security, or manufacturingCommon across tech, automotive, healthcare, and research sectors

The main difference lies in work hours and shift timing. Evening Computer Vision Deep Learning Engineers work primarily during evening or night shifts, often in environments requiring 24/7 monitoring or operations. In contrast, Computer Vision Deep Learning Engineers usually work standard daytime hours. Both roles require similar skills and educational backgrounds, but their schedules and work environments differ significantly.

More about Evening Computer Vision Deep Learning Engineer jobs
What cities are hiring for Evening Computer Vision Deep Learning Engineer jobs? Cities with the most Evening Computer Vision Deep Learning Engineer job openings:
What are the most commonly searched types of Computer Vision Deep Learning Engineer jobs? The most popular types of Computer Vision Deep Learning Engineer jobs are:
What states have the most Evening Computer Vision Deep Learning Engineer jobs? States with the most job openings for Evening Computer Vision Deep Learning Engineer jobs include:
What job categories do people searching Evening Computer Vision Deep Learning Engineer jobs look for? The top searched job categories for Evening Computer Vision Deep Learning Engineer jobs are:
Evening Computer Vision Deep Learning Engineer jobs near you
Infographic showing various Evening Computer Vision Deep Learning Engineer job openings in the United States as of June 2026, with employment types broken down into 2% Internship, 80% Full Time, 3% Part Time, 6% Temporary, and 9% Contract. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution, with an average salary of $121,515 per year, or $58.4 per hour.
Deep Learning Engineer

Deep Learning Engineer

Hayden AI

San Francisco, CA • On-site

$161K - $175K/yr

Full-time

Posted 12 days ago

Job description

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 Deep Learning Team
The Deep learning team's work is at the crux of Hayden AI's solutions to its customers. The team is responsible for building and maintaining advanced models that are able to perceive the world and the knowledge produced by the models is used downstream to implement various customer use-cases. The team runs a number of models both in the cloud as well as on the edge device serving different scenarios. The team also works closely with the platform team to build out Hayden AI's MLOps infrastructure to achieve better scale and reliability.
About the Role
As a Deep Learning Engineer at Hayden, you will make key contributions towards building foundational AI capabilities for Hayden that will enable solving complex problems for Hayden AI Customers. In this role, you will build, train, evaluate and deploy state of the art ML models in production at scale. You will report into the Director of AI within the Perception Org and work closely with other engineering as well as product teams to deliver value to Hayden AI customers. We are looking for someone who has familiarity with or growing expertise in at least one of the verticals below - depth in a specific area is valued but not required on day one.
  1. 3D vision models to predict depth and 3D structure,
  2. Video/temporal behavior models to predict intent,
  3. Deep understanding of Vision language models and hands-on experience fine tuning them,
  4. Deep understanding of foundation models in perception.
  5. Deep knowledge of Nvidia edge device stack for running ML models and cuda know-how in terms delivering highly optimized models

This position is based in San Francisco and follows a hybrid schedule with at least 3 days in-office per week.
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.
  • Come up with solutions to complex problems in perception using deep learning.
  • Articulate ideas both verbally and in written form culminating in clear design and project plan docs for their work
  • Contribute to team roadmap and planning
  • Work with cross functional teams across the company and contribute towards delivery of end to end solutions for the customer

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.
  • Experience: 1-2 years experience building and deploying machine learning models for perception in production settings.
  • Core Skills: Solid hands-on experience designing, training, and evaluating machine learning models for perception. Demonstrated ability to independently build ML pipelines and deploy models to cloud environments (AWS, GCP, or Azure); familiarity with MLOps practices including experiment tracking, model versioning, and automated workflows. Hands-on experience in PyTorch, Python, and related skills.
  • Personal Attributes:Good communicator, self starter and ability to collaborate with others, quick learner who can adapt to a fast paced startup culture
  • Education: Bachelors or Masters in Computer Science or related field
  • Nice to Have: Experience working in perception problems in self driving car companies that aligns closely with the work of this team.

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