Why This Role Stands Out
You will thrive as an Applied Computer Vision Engineer at Vantor, leveraging your expertise in Python, deep learning, and cloud platforms to build impactful vision solutions for web and cloud applications. This hybrid role offers significant opportunities for growth in ML and MLOps within a collaborative, low-ego team environment, enabling you to directly solve client problems and advance your skills. Apply now to join a reputable company and make a real difference in cutting-edge technology.
Quick Overview
Job Description
Vantor is seeking an Applied Computer Vision Engineer to design, build, and deploy vision solutions for modern web and cloud applications. You'll develop and productionize models for detection, tracking, and recognition while creating robust data and training pipelines. In this collaborative, low ego culture, you'll work closely with full stack, data, and cloud engineers to solve real client problems using agile practices. Expect hands on work with Python, deep learning frameworks, and cloud services, plus strong opportunities to grow in ML, MLOps, and scalable software delivery.
Responsibilities
- Design and implement computer vision models for client applications, including detection, tracking, and recognition tasks
- Build data pipelines for image/video ingestion, preprocessing, annotation, and model training at scale
- Integrate trained models into production web and cloud systems using modern APIs and services
- Collaborate with full stack, data, and cloud engineers to deliver end to end vision solutions
- Evaluate model performance, run experiments, and iteratively improve accuracy, latency, and robustness
- Deploy and monitor models in cloud environments, optimizing for scalability, reliability, and cost
- Work directly with clients and product owners to refine requirements and translate them into technical designs
- Write clean, maintainable code, tests, and documentation following agile and Dev
- Ops practices
Required Skills
- Computer vision
- Deep learning
- Python
- Py
- Torch or Tensor
- Flow
- Open
- CVMachine learning pipelines
- RESTful APIs
- Cloud platforms (AWS, Azure, or GCP)
- Docker and containerization
- MLOps and model deployment
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