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Computer Vision Deep Learning Jobs (NOW HIRING)

Duranta

Computer Vision Engineer

Seattle, WA · On-site

$160K - $225K/yr

Our flagship foundation computer vision model, Aidan, measures and understands the world in 4D ... You will work closely with the founding team on deep learning research and deployment across ...

Duranta

Computer Vision Engineer

Seattle, WA · On-site +1

$160K - $225K/yr

Our flagship foundation computer vision model, Aidan, measures and understands the world in 4D ... You will work closely with the founding team on deep learning research and deployment across ...

Carbon Robotics

Deep Learning Engineer

Seattle, WA

Lead the design and execution of experiments to develop and validate novel deep learning architectures for computer vision in agricultural environments * Own model optimization and deployment ...

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All JobsComputer Vision Deep Learning Jobs

Computer Vision Deep Learning information

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$33.5K

$48.3K

$63.5K

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

As of Jun 25, 2026, the average yearly pay for computer vision deep learning in the United States is $48,298.00, according to ZipRecruiter salary data. Most workers in this role earn between $38,000.00 and $55,500.00 per year, depending on experience, location, and employer.

What is computer vision deep learning?

Computer vision deep learning is a field of artificial intelligence that leverages deep neural networks to enable computers to interpret and understand visual information from the world, such as images and videos. By using deep learning techniques, such as convolutional neural networks (CNNs), systems can perform tasks like image classification, object detection, and facial recognition with high accuracy. This technology is widely applied in industries including healthcare, automotive, and security for tasks ranging from medical image analysis to autonomous driving.

What are some common challenges faced in a Computer Vision Deep Learning role, and how can they be addressed?

Professionals in Computer Vision Deep Learning often face challenges such as managing large, complex datasets, ensuring high model accuracy, and dealing with real-world variability in images or video. Addressing these issues typically involves data augmentation, careful preprocessing, and the use of advanced architectures like CNNs and transformers. Collaboration with data engineers and domain experts is essential to ensure data quality and to tailor solutions to specific use cases. Additionally, staying updated with the latest research and tools can help in overcoming technical hurdles and enhancing model performance.

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

AspectComputer Vision Deep LearningComputer Vision Engineer
Required CredentialsBachelor's or higher in CS, AI, or related fields; knowledge of deep learning frameworksBachelor's or higher in CS or related fields; experience with computer vision algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on AI modelsSoftware development teams, product companies, tech firms applying computer vision
Employer & Industry UsageAI research, academia, companies developing deep learning models for vision tasksProduct development, application of computer vision in real-world projects

Computer Vision Deep Learning specialists focus on developing and applying deep learning models for visual data analysis, often involving research and model training. In contrast, Computer Vision Engineers implement and optimize computer vision algorithms within products and applications, emphasizing deployment and practical use. Both roles require a strong foundation in computer vision, but their focus areas and work environments differ.

What are the key skills and qualifications needed to thrive as a Computer Vision Deep Learning Engineer, and why are they important?

To thrive as a Computer Vision Deep Learning Engineer, you need a strong background in mathematics, programming (especially Python), and deep learning concepts, often supported by a degree in computer science or a related field. Proficiency with frameworks like TensorFlow, PyTorch, OpenCV, and experience using GPU computing are highly valued, along with relevant certifications in machine learning or artificial intelligence. Strong analytical thinking, creative problem-solving, and effective communication skills set top candidates apart in this role. These competencies are essential for developing, optimizing, and deploying innovative computer vision solutions that address complex real-world challenges.
More about Computer Vision Deep Learning jobs
What job categories do people searching Computer Vision Deep Learning jobs look for? The top searched job categories for Computer Vision Deep Learning jobs are:
Computer Vision Deep Learning jobs near you
Infographic showing various Computer Vision Deep Learning job openings in the United States as of June 2026, with employment types broken down into 48% Full Time, 18% Part Time, and 34% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $48,298 per year, or $23.2 per hour.
Senior/Staff Computer Vision Engineer - Deep Learning Focus

Senior/Staff Computer Vision Engineer - Deep Learning Focus

Phantom AI

Mountain View, CA • Hybrid

$180K - $240K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 22 days ago

Job description

About Us

At Phantom AI, we've built a team of incredibly talented and ambitious people challenging the norm in the automotive industry. We are building cost-effective L2/L3 solutions to reduce the burden of everyday driving and make the roads safe for everyone. For instance, we believe democratizing technologies such as Automatic Emergency Braking and Emergency Lane Support is the first priority before tackling a fully self-driving vehicle. Our main customers are Tier 1 automotive manufacturers who are focused on delivering L2/L3 solutions and in the future will deliver full autonomy.

We differentiate ourselves from other autonomous driving startups through a combination of state-of-the-art technological know-how and real automotive experiences of shipping ADAS systems at a volume production scale. If you feel that you have the passion, commitment, and drive to challenge the status quo within the automotive industry, we would love to hear from you.

We are seeking a highly skilled Senior Deep Learning Engineer to drive the development and deployment of advanced perception models for Advanced Driver Assistance Systems (ADAS). The successful candidate will play a key role in designing cutting-edge neural network architectures, optimizing model performance, and ensuring reliable deployment on embedded platforms. This position requires a balance of deep technical expertise, strong analytical thinking, and cross-functional collaboration.


Responsibilities

  • Design and implement advanced deep learning architectures to enhance perception capabilities within ADAS systems.
  • Maintain and continuously improve existing models by optimizing performance, addressing issues, and refining architecture and algorithms.
  • Perform detailed root cause analysis of production issues and develop sustainable, high-quality solutions.
  • Optimize model performance with a focus on latency, efficiency, and resource utilization for real-time embedded deployment.
  • Integrate and validate deep learning algorithms on automotive-grade hardware and embedded SoCs.
  • Collaborate closely with data engineering, data annotation, and platform engineering teams to ensure smooth data flow and seamless model integration.
  • Provide regular updates and technical reports on model development, maintenance progress, and performance metrics to management.


Required Qualifications

  • 3–5+ years of professional experience developing, training, validating, and deploying deep learning-based perception models for ADAS or related computer vision applications.
  • In-depth understanding of training and inference pipelines, including data loading, augmentation, and loss function design.
  • Advanced degree (M.S. or Ph.D.) in Computer Vision, Robotics, Machine Learning, or a closely related discipline, or equivalent industry experience.
  • Strong proficiency in Python and a deep understanding of software design principles and development best practices.
  • Expertise in PyTorch (preferred) or TensorFlow for large-scale model development and experimentation.
  • Practical experience with data pipelines, distributed training, and machine learning experiment management tools.
  • Proven ability to work effectively in a collaborative, cross-functional team environment.


Preferred Qualifications

  • Comprehensive understanding of machine learning algorithms, including classification, regression, and clustering methods.
  • Experience deploying and optimizing models for embedded or automotive SoCs (e.g., NVIDIA Drive, TI TDA4, Qualcomm Snapdragon).
  • Proficiency in model optimization techniques such as quantization, pruning, and knowledge distillation.
  • Doctorate (Ph.D.) in Computer Science, Artificial Intelligence, or related field is a plus.
  • Strong programming experience in Python and/or C++ within Linux development environments.
  • Familiarity with automotive perception workflows, datasets, and evaluation frameworks (e.g., KITTI, Waymo, Euro NCAP)


Benefits

We offer our employees a comprehensive benefits package including:

  • Salary $180,000-$240,000
  • Medical, dental and vision coverage
  • Office snacks & reimbursable meals*
  • Paid Time Off
  • FSA
  • 401K


Work Type

Hybrid - Phantom AI follows this type of working experience to allow employees the flexibility to work weekly at the office 4x and from home 1x.


Equal Opportunity for Diversity & Inclusion

Phantom AI provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

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