Job Specifications
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. You'll 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 frameworks and deployments.
Using technologies like Kafka, Kinesis, Redis, or similar message brokers to feed our real-time model inference systems.
Operating large-scale distributed systems and microservice architectures in a production environment.
API design principles and hands-on experience building services with REST and/or gRPC.
Building scalable training pipelines and evaluation frameworks to implement CI/CD for ML and sophisticated production monitoring.
Go beyond model-level tuning to optimize the entire system stack, from network I/O and serialization to GPU utilization and autoscaling policies.
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 model infrastructure.
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 performance optimization of large models.
Bachelor's or Master's degree 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.
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
Bachelor's 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.
About the Company
OP is one of the fastest-growing technology consulting and solutions companies in the U.S. We offer advisory and managed services, innovative platforms, and staffing solutions to help clients harness the power of technology for maximum impact. With broad and deep industry expertise, we deliver solutions across AI, cybersecurity, enterprise architecture, and beyond.
We don't just consult--we challenge the norms of consulting. Our approach pairs out-of-the-box thinking with a radically lean model for faster, smarter, and more...
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