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Temporary Computer Vision Deep Learning Engineer Jobs

ISEE is seeking a full-time Machine Learning Engineer to join our team. The ideal candidate has ... in deploying Computer Vision/Deep learning algorithms in real-world scenarios. * Robotics ...

Deep Learning Engineer

Palo Alto, CA · On-site

$170K - $300K/yr

About Matroid Matroid is a full-service computer vision company that has developed an end-to-end ... We are looking for a world-class Deep Learning Software Engineer who is excited to operate at the ...

About Matroid Matroid is a full-service computer vision company that has developed an end-to-end ... We are looking for a world-class Deep Learning Software Engineer who is excited to operate at the ...

Senior Deep Learning Engineer - Perception

San Jose, CA · On-site

$123.70K - $169.90K/yr

Senior Deep Learning Engineer, Computer Vision imagry.E4.E30@comeetapply.com Location: San Jose, CA , On Site We are looking for a capable and experienced Sr. Deep Learning Engineer to join our R&D ...

... deep learning architectures for computer vision in agricultural environments * Own model ... Partner with Engineering and Product Management to scope, prioritize, and deliver high-impact ...

The Carbon Robotics LaserWeederâ„¢ leverages advanced robotics, computer vision, AI/deep learning ... Partner with Engineering and Product Management to scope, prioritize, and deliver high-impact ...

The Carbon Robotics LaserWeederâ„¢ leverages advanced robotics, computer vision, AI/deep learning ... Partner with Engineering and Product Management to scope, prioritize, and deliver high-impact ...

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Temporary Computer Vision Deep Learning Engineer information

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$48.5K

$121.5K

$137.5K

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

As of May 30, 2026, the average yearly pay for temporary 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 Temporary Computer Vision Deep Learning Engineer vs Computer Vision Engineer?

AspectTemporary Computer Vision Deep Learning EngineerComputer Vision Engineer
CredentialsBachelor's or Master's in CS, AI, or related; experience with deep learning frameworksBachelor's or Master's in CS, AI, or related; experience with computer vision tools
Work EnvironmentProject-based, short-term contracts, often in tech or research firmsFull-time, ongoing roles in tech companies, startups, or research labs
Industry UsageCommon in consulting, research projects, or temporary assignmentsStandard role in product development, AI solutions, and software engineering

The main difference is that a Temporary Computer Vision Deep Learning Engineer works on short-term projects focusing on deep learning techniques for computer vision, while a Computer Vision Engineer typically holds a permanent position involved in ongoing development of computer vision applications. The temporary role emphasizes flexibility and project-specific skills, whereas the full-time role involves continuous integration into a company's long-term projects.

More about Temporary Computer Vision Deep Learning Engineer jobs
What cities are hiring for Temporary Computer Vision Deep Learning Engineer jobs? Cities with the most Temporary 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 Temporary Computer Vision Deep Learning Engineer jobs? States with the most job openings for Temporary Computer Vision Deep Learning Engineer jobs include:
What job categories do people searching Temporary Computer Vision Deep Learning Engineer jobs look for? The top searched job categories for Temporary Computer Vision Deep Learning Engineer jobs are:
Infographic showing various Temporary Computer Vision Deep Learning Engineer job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 77% Full Time, 17% Part Time, 1% Temporary, and 4% Contract. Highlights an 90% Physical, 2% Hybrid, and 8% Remote job distribution, with an average salary of $121,515 per year, or $58.4 per hour.
Machine Learning Engineer

Machine Learning Engineer

ISEE

Remote

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

ISEE is seeking a full-time Machine Learning Engineer to join our team. The ideal candidate has several years of work experience.
Role responsibilities include:
  • Working on the intersection of sensing and perception algorithms.
  • Prototyping and deploying robust computer vision algorithms on ISEE's vehicle fleet in areas of: Sensor calibration, localization and mapping, fusion, tracking and pattern recognition.
  • Benchmarking and maintaining developed modules.
  • Work independently to deliver high-quality code in a timely fashion.
  • Collaborate with team for testing, evaluation and review of code.

Required Qualifications
  • Degree in Computer Science, Electrical Engineering, Robotics or related field.
  • Experience in deploying deep learning models at scale on real-world data in at least one of these deep learning frameworks: PyTorch, Tensorflow, Caffe.
  • Hands-on experience with developing, training and deploying deep learning models in multimodal (sensors space and temporal) real world data.
  • Strong Python and/or C++ skills.
  • Passionate about self-driving vehicles and real-world robotic solutions.
  • Strong presentation and communication skills.

Preferred
  • Publication record in top-tier computer vision or machine learning conferences.
  • 3+ yrs industrial experience in deploying Computer Vision/Deep learning algorithms in real-world scenarios.
  • Robotics/autonomous experience is a plus.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.