About the Role
Join OP as a Computer Vision Pipeline Engineer, where you’ll bring advanced vision systems to life. This role blends deep learning with infrastructure engineering to develop and deploy high-performance computer vision (CV) models. You’ll build scalable training and deployment pipelines that support real-world CV solutions.
Core Responsibilities
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Deploy and optimize large-scale models like YOLO and OWL for real-time applications.
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Create robust training and deployment systems using Kubernetes and Ubuntu.
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Tune hyperparameters and refine models to balance speed, accuracy, and resource use.
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Build tools for monitoring and evaluating models within a modern MLOps framework.
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Work cross-functionally to integrate models into production and automate ML workflows.
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Stay up to date on cutting-edge CV research and apply it to model improvements.
Required Skills & Experience
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Strong Python and PyTorch skills.
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Practical experience with object detection using YOLO and OWL.
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Solid knowledge of CV tasks such as detection, segmentation, and classification.
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Skilled in Kubernetes, Docker, AWS SageMaker, and Linux (Ubuntu).
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Familiar with MLOps tools like MLflow or Weights & Biases.
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Experience tuning large models and deploying at scale.
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Bachelor’s or Master’s in CS, ML, or related field (PhD or research experience is a plus).
Preferred Skills
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Experience with real-time or edge inference (e.g., ONNX Runtime, TensorRT, Jetson).
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Familiarity with distributed training environments.
Benefits
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401(k), health, dental, and vision insurance.
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Inclusive and diverse work culture.
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Salary based on experience, skills, and location.
Additional Involvement
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Join team meetings and technical discussions.
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Contribute to shared documentation and collaboration platforms.
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Provide status updates to the account management team.
About OP
OP is a consulting and technology services firm specializing in AI, cybersecurity, enterprise architecture, and more. They offer advisory and managed services, platforms, and staffing. OP values innovation, collaboration, and excellence—and looks for team members who share that mindset.