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Computer Vision Scientist Jobs (NOW HIRING)

SID Global Solutions

Computer Vision Engineer

Bellevue, WA · On-site

$125K - $148K/yr

Collaborate with Scientists to create advanced simulation models and perform "what-if" scenario ... Must-Have Qualifications Proven experience in computer vision (CV) and machine learning (ML ...

Zobility

Computer Vision Engineer

Raymond, OH · On-site

$108K - $127K/yr

They are seeking a Computer Vision Engineer to develop and implement digital technology solutions ... science, data science or equivalent experience. Company : Zobility is a talent management and ...

TEEMA

Computer Vision Engineer

San Diego, CA · On-site

$125K - $130K/yr

Bachelor's or Master's in Computer Science, Computer Engineering, Electrical Engineering, or related field * 3+ years of computer vision experience in real-time, product-focused environments * Strong ...

EE Recruiters

Computer Vision Engineer

Santa Clara, CA

$131K - $155K/yr

S./Ph.D. in computer sciences or related area with at least 2 years of working experience in industry * 2+ years of experience with machine learning, computer vision, and signal processing

Infosys Limited Digital

Computer Vision Engineer

Grapevine, TX · On-site

$103K - $121K/yr

... science|Computer Vision Technical Skills 2 Technology|data science|PYTHON Technical Skills 3 Technology|Traditional AI|TensorFlow Overview The Infosys Engineering unit is dedicated to amplifying ...

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Computer Vision Scientist information

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$50.5K

$111.3K

$137.5K

How much do computer vision scientist jobs pay per year?

As of Jul 14, 2026, the average yearly pay for computer vision scientist in the United States is $111,343.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,500.00 and $137,000.00 per year, depending on experience, location, and employer.

What is the difference between Computer Vision Scientist vs Machine Learning Engineer?

AspectComputer Vision ScientistMachine Learning Engineer
Required CredentialsMaster's or PhD in Computer Science, AI, or related fieldsBachelor's or Master's in Computer Science, Software Engineering, or related fields
Work EnvironmentResearch labs, R&D departments, academiaProduct teams, software development environments
Industry UsageDeveloping algorithms for image/video analysis, object detectionBuilding scalable ML models for various applications including vision

While both roles involve machine learning, Computer Vision Scientists focus on developing algorithms specifically for visual data, whereas Machine Learning Engineers implement and deploy these models in real-world applications. The roles often overlap but differ mainly in their primary focus and work environment.

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

A Computer Vision Scientist needs a strong background in mathematics, machine learning, and image processing, often supported by a graduate degree in computer science or a related field. Familiarity with deep learning frameworks (such as TensorFlow or PyTorch), programming languages like Python or C++, and experience with libraries like OpenCV are typically required. Creative problem-solving, critical thinking, and effective communication help distinguish top performers in this role. These skills are essential for developing innovative computer vision solutions that can be effectively integrated into real-world applications.

What are some common challenges faced by Computer Vision Scientists when deploying models to production environments?

Computer Vision Scientists often encounter challenges such as ensuring model robustness under varying real-world conditions, optimizing inference speed for deployment on resource-constrained devices, and managing large-scale data for continuous model improvement. Collaboration with engineering teams is crucial to integrate models efficiently into existing software pipelines and to address issues like latency and scalability. Additionally, maintaining high accuracy while minimizing false positives and negatives in live environments requires ongoing monitoring and iterative improvement.

What are Computer Vision Scientists?

Computer Vision Scientists are professionals who develop algorithms and models that allow computers to interpret and understand visual information from the world, such as images and videos. They use techniques from machine learning, artificial intelligence, and image processing to solve problems like object detection, facial recognition, and scene understanding. Their work is essential in fields such as autonomous vehicles, healthcare imaging, robotics, and augmented reality. Computer Vision Scientists often collaborate with engineers and domain experts to create practical applications and improve existing technologies.
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What states have the most Computer Vision Scientist jobs? States with the most job openings for Computer Vision Scientist jobs include:
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Computer Vision Scientist jobs near you
Computer Vision Engineer

Computer Vision Engineer

SID Global Solutions

Bellevue, WA • On-site

$125K - $148K/yr

Full-time

Re-posted 8 days ago

Job description

Role Overview We are seeking a highly skilled and innovative Computer Vision Engineering to lead the lifecycle of complex cross-functional projects within our North America Fulfillment Network. This role focuses on designing, developing, and implementing advanced engineering solutions, integrating IIoT hardware, computer vision, and machine learning to improve material handling, operator workflows, and fulfillment processes. The ideal candidate has a strong background in engineering design, computer vision, and applied machine learning, with proven experience driving large-scale projects, collaborating across teams, and delivering impactful outcomes in dynamic operational environments.

Key Responsibilities Lead and manage end-to-end life cycles of complex cross-functional projects spanning organizations and geographies, ensuring delivery of impactful business outcomes. Engineering Solutions: Design and develop engineering solutions for material handling challenges, considering human-equipment interactions and operational excellence. IIoT Development: Develop, configure, and implement IIoT hardware to enhance equipment, processes, and operator workflows.

Simulation & Modeling: Collaborate with Scientists to create advanced simulation models and perform "what-if" scenario testing to drive optimal hardware and process solutions. Concept & Design Leadership: Lead concept efforts for optimal solutions including equipment specifications, material flow, ergonomics, associate experience, operational considerations, and site layout. Vendor & Stakeholder Collaboration: Partner with suppliers, vendors, and internal teams to deliver innovative solutions with scalability and efficiency.

Documentation & Standards: Ensure all solutions are documented with SOPs and/or structured change control, setting standards for engineering excellence. Multi-Project Management: Manage multiple initiatives simultaneously while influencing, negotiating, and communicating effectively with internal and external stakeholders. Thought Leadership: Deliver artifacts (research, schematics, prototypes, 3D models, analysis, test plans, narratives) that set benchmarks for organizational engineering standards.

Consensus Building: Communicate complex ideas clearly, harmonize diverse perspectives, and build consensus to resolve contentious issues. Must-Have Qualifications Proven experience in computer vision (CV) and machine learning (ML) integration for real-time solutions. Strong coding skills (Python, C++, or similar) with the ability to prototype, test, and deploy ML/CV models in production environments.

Demonstrated ability to lead large-scale engineering projects or device development from concept through implementation. Hands-on experience with IIoT hardware design, configuration, and integration for operational improvements. Strong knowledge of system design, material handling, and human-machine interaction principles.

Exceptional program management, communication, and stakeholder management skills. Nice-to-Have Qualifications Advanced Python programming skills for data modelling, simulation, and rapid prototyping. Experience with system emulation and testing environments.

Strong background in cross-functional collaboration within large, fast-paced, and dynamic operational environments. Familiarity with 3D modelling, CAD tools, or hardware prototyping.

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