Computer Vision Engineer – Bengaluru | WFO (6 Days) |

End-to-end computer vision engineer responsible for building, deploying, and monitoring real-time video analytics systems on edge and Linux environments. Role involves model development (detection, segmentation, classification, tracking), optimization for real-time inference, and integration via APIs for production-grade deployments.

Key Responsibilities

- Build production computer vision systems end-to-end from requirements gathering through data preparation, model development, deployment, and monitoring.
- Develop and fine-tune models for object detection, segmentation, classification, and tracking.
- Handle data quality aspects and work with evaluation metrics such as mAP, IoU, Dice, precision/recall, and F1 score.
- Deploy real-time video processing pipelines using tools such as OpenCV, GStreamer, and FFmpeg.
- Optimize model inference using ONNX, TensorRT, and OpenVINO for real-time and edge scenarios.
- Build APIs using FastAPI or Flask and deploy services on Linux environments, leveraging Docker where applicable.
- Collaborate with backend teams, clearly communicate technical trade-offs, and integrate CV components into larger systems.
- Work effectively in a research-driven environment while maintaining a hands-on builder mindset.
- Contribute to monitoring and logging of deployed CV/ML systems, potentially using tools like MLflow or Weights & Biases.





Must-Have Skills

- Approximately 2 years of hands-on computer vision / machine learning engineering experience
- Strong Python programming skills
- Solid FastAPI skills for API development
- Experience in at least one of: detection, segmentation, tracking, or classification models.
- Robust experience with PyTorch
- Understanding and practical use of evaluation metrics such as mAP, IoU, Dice, precision/recall, and F1
- Experience with deployment on Linux environments
- Ability to debug models and pipelines using metrics and logs
- Strong problem-solving skills
- Ability to work in research-driven environments
- Hands-on builder mindset
- Good communication skills

Nice-to-Have Skills

- Experience with GStreamer, FFmpeg, and RTSP streaming
- Experience with ONNX, TensorRT, and OpenVINO for model optimization
- Edge deployment experience (e.g., NVIDIA Jetson, ARM, embedded Linux)
- Familiarity with YOLO, Detectron2, ViT/Swin, SAM, and CLIP
- Docker and CI/CD experience
- Experience with annotation tools such as CVAT and Label Studio
- Experience with MLflow or Weights & Biases
- Experience with monitoring and logging systems for ML/CV pipelines
- Familiarity with LLMs, speech AI, and edge deployment (as part of broader exposure in the environment)

Pay: ₹800,000.00 - ₹1,000,000.00 per year

Work Location: In person

📌 Computer Vision Engineer (India)
🏢 McLaren Strategic Solution
📍 India