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Full Time Computer Vision Deep Learning Engineer Jobs

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 ...

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 ...

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

As a Deep Learning Engineer, you will design, develop, and deploy deep learning systems for ... for computer vision in agricultural environments • Own model optimization and deployment ...

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Full Time Computer Vision Deep Learning Engineer information

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$48.5K

$121.5K

$137.5K

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

As of Aug 20, 2026, the average yearly pay for full time 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 Full Time Computer Vision Deep Learning Engineer vs Machine Learning Engineer?

AspectFull Time Computer Vision Deep Learning EngineerMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, AI, or related; experience with CV and DL frameworksBachelor's or Master's in CS, Data Science, or related; strong programming skills
Work EnvironmentResearch labs, tech companies, AI startups focusing on visual dataTech firms, finance, healthcare, focusing on predictive models
Industry UsagePrimarily in computer vision, robotics, autonomous vehiclesBroader, including NLP, recommendation systems, predictive analytics

The main difference is that Full Time Computer Vision Deep Learning Engineers specialize in visual data analysis using deep learning, while Machine Learning Engineers work on a wider range of predictive models across various data types. Both roles require strong programming skills and knowledge of ML frameworks, but their focus areas and applications differ.

More about Full Time Computer Vision Deep Learning Engineer jobs

What cities are hiring for Full Time Computer Vision Deep Learning Engineer jobs?

Cities with the most Full Time 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:

Infographic showing various Full Time 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.

Computer Vision / Deep Learning Scientist (Atlanta)

Aptonet

Atlanta, GA • On-site

Full-time

Posted 2 days ago

New


Job description

Computer Vision / Deep Learning Scientist – SeniorPosition Overview

We are seeking a Senior Computer Vision / Deep Learning Scientist to design, develop, and deploy advanced computer vision and deep learning solutions for unique, high-impact applications. The successful candidate will combine strong theoretical knowledge with hands‑on industry experience to develop novel algorithms, custom deep learning architectures, and production‑ready machine learning solutions. This role will be a key contributor to a Digital Train Inspection project, applying computer vision and deep learning techniques to analyze visual data and support automated inspection capabilities.

The Senior Scientist will own the model development lifecycle from requirements gathering and data evaluation through model development, validation, production integration, and post‑production support. The role requires close collaboration with application development teams, business stakeholders, and senior leadership, as well as the ability to provide technical guidance to junior team members and lead targeted research initiatives.

Work Arrangement
  • Hybrid schedule: Two days onsite each week for candidates located in the Atlanta area.
  • Fully remote option available for candidates located outside the Atlanta area.
Key Responsibilities
  • Design, develop, and implement novel computer vision algorithms for specialized and unique use cases.
  • Design and build custom deep learning architectures tailored to specific business and technical requirements.
  • Develop and apply deep learning models for semantic segmentation, object detection, image classification, and related computer vision applications.
  • Evaluate model accuracy, robustness, quality, and performance, as well as the quality and suitability of underlying data sources.
  • Develop clean, scalable, maintainable, and production‑ready Python and machine learning code.
  • Partner with application development teams to integrate computer vision and deep learning models into existing applications and production environments.
  • Own the complete model development lifecycle, including requirements gathering, data assessment, experimentation, model development, validation, deployment, monitoring, and post‑production support.
  • Conduct research and experimentation to identify and implement new computer vision and deep learning techniques.
  • Communicate technical findings, model performance, research results, and recommendations clearly to colleagues, business partners, and senior management.
  • Provide technical guidance and mentorship to junior team members and oversee targeted research and team projects.
  • Contribute to hiring initiatives, including technical candidate evaluation, interviews, and assessment of prospective team members.
  • Collaborate across technical and business functions to translate complex computer vision challenges into practical, scalable solutions.
Required Qualifications
  • Bachelor’s, Master’s, or Ph.D. in Computer Science, Electrical Engineering, Machine Learning, Statistics, or a related technical field.
  • 1–3 years of relevant industry experience in a role such as Computer Vision Scientist, Data Scientist, Research Scientist, Machine Learning Scientist, or similar; 3+ years of experience is preferred. Candidates with equivalent proven qualifications may also be considered.
  • Excellent programming skills in Python, with demonstrated experience developing machine learning or deep learning solutions in an industry environment.
  • Hands‑on industry experience with PyTorch or another major deep learning framework.
  • Strong practical experience applying deep learning techniques to computer vision problems, including semantic segmentation, object detection, and image classification.
  • Ability to evaluate model performance and data quality and translate findings into actionable improvements.
  • Experience developing production‑ready machine learning solutions and collaborating with software/application development teams.
  • Strong analytical, problem‑solving, communication, and research skills.
Preferred Qualifications
  • 3+ years of professional experience in computer vision, machine learning, deep learning, or a closely related discipline.
  • Experience taking machine learning models from research or experimentation into production.
  • Experience working with large‑scale visual datasets and establishing data quality and model evaluation processes.
  • Experience mentoring technical professionals or leading research‑oriented projects.
  • Experience participating in technical recruiting, interviewing, or candidate evaluation.
Project Focus: Digital Train Inspection

The selected candidate will contribute to a Digital Train Inspection initiative, developing computer vision and deep learning capabilities that support automated analysis of train and rail‑related visual inspection data. The work will involve applying advanced image analysis and machine learning techniques to identify, classify, segment, and evaluate visual conditions relevant to inspection and maintenance workflows.

Core Technical Skills
  • Python
  • PyTorch or comparable deep learning frameworks
  • Computer Vision
  • Semantic Segmentation
  • Image Classification
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