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Computer Vision Machine Learning Jobs (NOW HIRING)

Apple

Machine Learning/Computer Vision Engineer

Sunnyvale, CA · On-site

$130K - $154K/yr

Our team delivers computer vision and machine learning algorithms that power many Apple technologies like human understanding and human intelligence algorithms with applications for digital humans ...

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Computer Vision Machine Learning information

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$12

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How much do computer vision machine learning jobs pay per hour?

As of Jun 20, 2026, the average hourly pay for computer vision machine learning in the United States is $19.92, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $21.88 per hour, depending on experience, location, and employer.

Is computer vision a dead field?

Computer vision is an active and rapidly evolving field within machine learning, with ongoing research and industry applications in areas like autonomous vehicles, healthcare, and security. Professionals in this area often work with deep learning frameworks such as TensorFlow or PyTorch and require strong programming skills. The demand for computer vision expertise continues to grow as technology advances.

What engineers make $500,000?

Senior computer vision machine learning engineers with extensive experience, advanced skills in deep learning frameworks, and a strong track record in deploying scalable AI systems can earn salaries approaching or exceeding $500,000, especially in high-cost-of-living areas or within large tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on product development.

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

To thrive as a Computer Vision Machine Learning Engineer, you need strong foundations in mathematics, programming (especially Python or C++), and expertise in machine learning algorithms, typically supported by a degree in computer science, engineering, or a related field. Familiarity with deep learning frameworks like TensorFlow or PyTorch and experience with image processing libraries are essential, along with knowledge of version control systems. Strong problem-solving, collaboration, and communication skills help you translate complex requirements into effective models and work efficiently in multidisciplinary teams. These skills ensure the development of robust computer vision solutions that address real-world challenges and drive innovation.

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

Computer Vision Machine Learning engineers often encounter challenges such as ensuring models perform well on real-world, diverse image data that may differ from training datasets. Managing computational efficiency and latency is crucial, especially for real-time applications. Additionally, integrating models with existing software systems and maintaining accuracy as data evolves can be complex. Collaboration with data engineers, software developers, and product teams is essential to address these challenges and ensure smooth deployment and monitoring.

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

AspectComputer Vision Machine LearningData Scientist
Required CredentialsBachelor's or higher in CS, ML, or related; experience with ML frameworksBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentResearch labs, tech companies, AI startups focusing on visual dataBusiness, finance, healthcare sectors analyzing diverse data sets
Industry UsageDeveloping visual recognition systems, image processingData analysis, predictive modeling, business insights
Common Search/ComparisonYesYes

While both roles involve machine learning, Computer Vision Machine Learning specializes in visual data and image processing, whereas Data Scientists work with a broader range of data types to generate insights across various industries.

Which has more salary, CS or AI?

Computer Vision Machine Learning roles, often within AI, tend to have higher salaries than general computer science positions due to specialized skills in deep learning, neural networks, and data analysis. AI roles typically require advanced knowledge of algorithms and tools like TensorFlow or PyTorch, which are highly valued in the job market. Salary differences can vary based on experience, location, and industry, but AI-focused positions generally offer higher compensation.

Which 5 jobs will survive AI?

For a Computer Vision Machine Learning role, jobs that require complex problem-solving, creativity, and human judgment are more likely to persist, such as research scientists, AI ethics specialists, data engineers, software developers, and domain-specific analysts. These roles often involve tasks that are difficult to automate fully and benefit from specialized expertise, continuous learning, and adaptability. Skills in programming, deep learning frameworks, and understanding of real-world applications remain valuable in these positions.

What is a Computer Vision Machine Learning Engineer?

A Computer Vision Machine Learning Engineer is a professional who develops algorithms and models that enable computers to interpret and understand visual data from the world, such as images and videos. They use techniques from machine learning, deep learning, and image processing to build systems capable of tasks like object detection, image classification, facial recognition, and scene understanding. Their work is critical in fields such as autonomous vehicles, healthcare imaging, security, and augmented reality. These engineers typically have strong skills in programming, mathematics, and data analysis, and often work closely with data scientists and software developers.
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Computer Vision Machine Learning jobs near you
Computer Vision/Machine Learning Engineer

Computer Vision/Machine Learning Engineer

The Select Group

Cupertino, CA • On-site

$137K - $162K/yr

Other

Posted 16 days ago

Job description

Computer Vision / Multimodal AI Engineer
The Select Group is looking to add a Computer Vision and Multimodal AI Engineer to a highly innovative AI team to help shape the next generation of intelligent, AI-powered business solutions.
This is an opportunity to work on complex, real-world challenges at the intersection of Computer Vision, Vision-Language Models (VLMs), NLP, and agentic AI. Rather than maintaining existing systems, this individual will help build and scale new capabilities that transform visual information into actionable insights and business value.
We are seeking someone who enjoys experimentation, thrives in ambiguity, and can take an idea from concept through production deployment. Success in this role will come from a combination of technical depth, curiosity, and the ability to translate cutting-edge AI technologies into practical solutions that users can rely on every day.
What You'll Be Helping Build
  • Intelligent systems that analyze and understand visual data at scale.
  • Multimodal AI solutions that combine images, language, and reasoning to deliver richer insights.
  • Agentic AI workflows capable of surfacing recommendations and automating decision-making processes.
  • Production-grade AI applications that support both operational efficiencies and customer-facing experiences.
  • Scalable architectures that enable rapid experimentation while supporting long-term growth.

What Success Looks Like
The right person will be comfortable owning the full lifecycle of machine learning initiatives-from designing experiments and validating assumptions to deploying models and continuously improving performance.
This role will have significant influence on how AI solutions are architected, evaluated, and scaled. Strong candidates are naturally inquisitive, enjoy investigating why models succeed or fail, and can turn those findings into measurable improvements.
Technical Environment
  • Computer Vision and Machine Learning
  • Vision-Language Models (CLIP, BLIP, Gemini, and similar frameworks)
  • Multimodal AI and reasoning systems
  • Agentic AI workflows
  • Python
  • PyTorch, TensorFlow, CoreML, or similar ML frameworks
  • Cloud-based AI deployment environments
  • Model evaluation, optimization, and performance tuning

Who Tends to Excel in This Environment
  • Engineers who have successfully deployed machine learning solutions into production.
  • Professionals who enjoy building and testing new ideas rather than simply maintaining existing systems.
  • Individuals who can move comfortably between research, experimentation, engineering, and business conversations.
  • Practitioners who are excited about emerging technologies in multimodal AI, visual reasoning, and autonomous agents.
  • Self-starters who can operate independently while collaborating effectively across engineering, product, and business teams.

Why This Opportunity Stands Out
  • Work on some of the most rapidly evolving areas of artificial intelligence.
  • Opportunity to influence architecture, strategy, and technical direction.
  • Exposure to Computer Vision, multimodal AI, VLMs, and agentic systems in production environments.
  • Collaborative team culture that values experimentation, innovation, and measurable business impact.
  • Long-term engagement supporting the development of next-generation AI capabilities.
TSG is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. #LI-AM1
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