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Entry Level Computer Vision Deep Learning Engineer Jobs

Imagry

Senior Deep Learning Engineer - Perception

San Jose, CA · On-site

$123K - $169K/yr

Description 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 ...

Imagry

Senior Deep Learning Engineer - Perception

San Jose, CA · On-site

$123K - $169K/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 ...

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Entry Level Computer Vision Deep Learning Engineer information

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$48.5K

$121.5K

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

As of Aug 20, 2026, the average yearly pay for entry level 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 does an entry level computer vision deep learning engineer do?

An Entry Level Computer Vision Deep Learning Engineer works on developing and implementing algorithms that allow computers to interpret and understand visual information from the world, such as images or videos. They typically use deep learning techniques, especially neural networks, to build models for tasks like object detection, facial recognition, and image classification. Their responsibilities may include data preprocessing, model training and evaluation, writing code (often in Python), and collaborating with senior engineers on real-world projects. This role is ideal for those who have a strong foundation in machine learning, programming, and mathematics, but are just starting their careers in the field.

What types of projects do entry level computer vision deep learning engineers typically work on, and how is their work structured within a team?

As an entry-level Computer Vision Deep Learning Engineer, you can expect to contribute to projects like object detection, image classification, and model optimization for real-world applications. Your tasks may include data preprocessing, training and evaluating neural networks, and writing code to integrate models into products or pipelines. You'll often collaborate closely with senior engineers, data scientists, and product managers, typically working in agile teams where regular code reviews and knowledge sharing are common. This collaborative environment not only helps you learn best practices but also provides opportunities to gradually take on more responsibility as your skills develop.

What are the key skills and qualifications needed to thrive as an entry level computer vision deep learning engineer, and why are they important?

To thrive as an Entry Level Computer Vision Deep Learning Engineer, you need a solid understanding of computer vision fundamentals, deep learning concepts, and programming skills in languages like Python, along with a relevant degree in computer science, engineering, or a related field. Familiarity with frameworks such as TensorFlow or PyTorch, experience with OpenCV, and knowledge of version control systems like Git are typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help you collaborate within teams and tackle complex challenges. These skills and qualities are crucial for developing, deploying, and optimizing computer vision solutions that meet real-world business needs.
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Entry Level Computer Vision Deep Learning Engineer jobs near you
Infographic showing various Entry Level Computer Vision Deep Learning Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 16% Part Time, and 6% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $121,515 per year, or $58.4 per hour.

Machine Learning Engineer

PROPRIUS

San Francisco, CA

Full-time

Re-posted 6 days ago

Job description

Machine Learning Engineer

Location: San Francisco, CA

Sponsorship: No

Relocation: No

Industry: Machine Learning

Join an artificial intelligence company in San Francisco that excels at visual recognition and is looking for a new ML engineer to join their team. Become part of a collaborative team that tackles research problems through a process of prototyping, implementation, measurement, and iteration. You will implement state-of-the-art deep learning techniques to help develop innovative AI products.

As a ML Engineer, you will:

  • Work with the research team to improve the visual search products
  • Train models with curated data to evaluated and ultimately improve performance
  • Deploy production-ready models to customers
  • Help maintain the machine learning infrastructure

For this role you will need:

  • MS. Degree
  • Experience with Python
  • Computer Vision or NLP experience
  • Experience debugging complex systems.
  • (Kuberentes or Docker experience would be a plus).

This is an amazing opportunity to join a team and work on large projects using powerful computer vision/deep learning technology.

PROPRIUS is an AI Industry recruiting firm. We’re lucky enough to recruit the best candidates into the most exciting companies all over the United States. We deliver performance.