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Machine Learning Engineer - Computer Vision Jobs

88 Job Offers

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Machine Learning Engineer
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United States , Palo Alto
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Zyphra
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Machine Learning Engineering Manager, Recommendations
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United States , San Francisco
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280000.00 - 350000.00 USD / Year
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Suno
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Data & AI Architect Principal
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Hungary , Budapest
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Plusnet
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Head of AI / AI Tech Lead
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United States , San Francisco
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Darwin Recruitment GmbH
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Head of AI / AI Tech Lead
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United States , New York
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Darwin Recruitment GmbH
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Senior Data Scientist
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Australia , Sydney; Melbourne; Brisbane; Hobart
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UpGuard
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Software Development Manager, Autonomous Agentic Bidding
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United States , Palo Alto
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166400.00 - 287700.00 USD / Year
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Amazon Pforzheim GmbH
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Senior Platform Manager, Trust and Safety
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United States
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177000.00 - 208000.00 USD / Year
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Airbnb
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Data Scientist - Digital
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United States
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75000.00 - 85000.00 USD / Year
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Abercrombie & Fitch Co.
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Ai Architect
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Zoolatech
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Ai Architect
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Turkey , Istanbul
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Zoolatech
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Ai Architect
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Poland , Wroclaw
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ML Practice Leader (GenAI)
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Provectus
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AI Project Manager
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Germany , Düsseldorf
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Freshcells
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Senior Product Manager
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United States
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Follett Software
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Data Science Manager
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France , Paris
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Artelys
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Principal Product Manager, Growth
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United States , Atlanta
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180000.00 - 248000.00 USD / Year
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PagerDuty
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Staff Product Manager, Data Platform
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United States , San Francisco
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207000.00 - 244000.00 USD / Year
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Checkr
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Senior Principal Product Manager, Confluence AI
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United States , San Francisco
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183200.00 - 294400.00 USD / Year
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Senior Data Scientist - AI Modeling
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United States
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104000.00 - 143000.00 USD / Year
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Baxter
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Explore cutting-edge Machine Learning Engineer - Computer Vision jobs and launch your career at the intersection of artificial intelligence and visual data interpretation. Machine Learning Engineers specializing in Computer Vision are the architects behind systems that enable machines to see, interpret, and understand the visual world. This dynamic profession involves designing, building, and deploying sophisticated models that can process, analyze, and extract meaningful information from images and video streams. Professionals in these roles typically engage in the entire machine learning lifecycle, tailored for visual data. Common responsibilities include developing and training deep learning models, such as convolutional neural networks (CNNs), transformers, and object detection frameworks like YOLO or Faster R-CNNs. They work on tasks like image classification, object detection and tracking, semantic segmentation, facial recognition, and 3D reconstruction. A significant part of the role involves data engineering—collecting, cleaning, and augmenting large-scale image/video datasets to ensure model robustness. Engineers then optimize these models for performance and efficiency, often deploying them to production environments on cloud platforms, edge devices, or embedded systems, requiring close collaboration with software and MLOps teams. To succeed in Machine Learning Engineer - Computer Vision jobs, a strong foundation in both theoretical and applied disciplines is essential. Typical requirements include an advanced degree in Computer Science, Electrical Engineering, or a related field, coupled with proficiency in programming languages like Python and frameworks such as TensorFlow, PyTorch, or OpenCV. A deep understanding of linear algebra, calculus, probability, and neural network architectures is crucial. Furthermore, skills in software engineering best practices, version control (Git), and cloud services (AWS, GCP, Azure) are highly valued. Successful candidates also possess strong problem-solving abilities to tackle challenges in model accuracy, computational efficiency, and real-world deployment. The demand for talent in this field is rapidly growing across industries like autonomous vehicles, healthcare diagnostics, robotics, augmented reality, and smart surveillance. For those passionate about pushing the boundaries of how machines perceive the world, pursuing Machine Learning Engineer - Computer Vision jobs offers a rewarding path to innovation. Start your search today to find a role where you can transform pixels into actionable intelligence and build the intelligent systems of tomorrow.

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