Computer Vision Pipeline Engineer
Computer Vision Pipeline Engineer
Posted on :
14-07-2025
Employer Active
1 Vacancy
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Monthly Salary
Not Disclosed
Salary Not Disclosed
Vacancy
1 Vacancy
Posted on :
14-07-2025
Job Description
Bring cutting-edge vision to life as a highly skilled Computer Vision Pipeline Engineer! This dynamic role combines deep learning expertise with infrastructure engineering to develop experiment with and deploy state-of-the-art CV models. Youll be at the core of building scalable training evaluation and deployment pipelines that power real-world computer vision applications.
Key Responsibilities:
- Deploy large-scale computer vision models including YOLO and OWL optimizing for performance and efficiency.
- Design and implement robust training pipelines and deployment frameworks using tools such as Kubernetes and Ubuntu-based environments.
- Perform advanced hyperparameter tuning and model optimization to meet accuracy latency and compute requirements.
- Build reusable tools for model evaluation and monitoring within an MLOps workflow.
- Collaborate with cross-functional teams to integrate models into scalable production systems and automate the lifecycle of machine learning models.
- Stay current with the latest CV research (e.g. foundation models prompt-based detection) and apply insights into model development.
Required Skills & Qualifications:
- Proficiency in Python and deep learning frameworks especially PyTorch.
- Strong hands-on experience with YOLO (You Only Look Once) and OWL (Open-World Localization) object detection models.
- Solid understanding of computer vision tasks: object detection segmentation classification.
- Experience deploying models using Kubernetes Docker and AWS SageMaker.
- Familiarity with MLOps tools such as MLflow or Weights & Biases.
- Expertise in Ubuntu/Linux environments for ML/AI experimentation and deployment.
- Demonstrated success in hyperparameter tuning for large models.
- Bachelors or Masters in Computer Science Machine Learning or a related field. A PhD or research experience is a plus.
Key Skills:
- YOLO OWL.
- Python PyTorch.
- Kubernetes Ubuntu.
- Hyperparameter Tuning.
- MLOps.
- AWS SageMaker.
- Event-Driven Microservices.
Preferred Qualifications:
- Experience with real-time inference and edge deployment (e.g. TensorRT ONNX Runtime Jetson).
- Familiarity with distributed training frameworks.
Required Education:
- Bachelors Degree or equivalent.
Benefits:
- 401(k).
- Dental Insurance.
- Health insurance.
- Vision insurance.
- We are an equal-opportunity employer and value diversity equality inclusion and respect for people.
- The salary will be determined based on several factors including but not limited to location relevant education qualifications experience technical skills and business needs.
Additional Responsibilities:
- Participate in OP monthly team meetings and participate in team-building efforts.
- Contribute to OP technical discussions peer reviews etc.
- Contribute content and collaborate via the OP-Wiki/Knowledge Base.
- Provide status reports to OP Account Management as requested.
About us:
OP is a technology consulting and solutions company offering advisory and managed services innovative platforms and staffing solutions across a wide range of fields - including AI cybersecurity enterprise architecture and beyond. Our most valuable asset is our people: dynamic creative thinkers who are passionate about doing quality work. As a member of the OP team you will have access to industry-leading consulting practices strategies & and technologies innovative training & education. An ideal OP team member is a technology leader with a proven track record of technical excellence and a strong focus on process and methodology.
Employment Type
Full-time
Key Skills
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