Computer Vision Engineer

About Valiance

Valiance is a deeptech AI company building sovereign and mission-critical AI solutions for enterprises, public sector, and government institutions. 150+ engineers and data scientists. Google Cloud Partner. NASSCOM AI GameChangers Award winner. Aegis Graham Bell Award for Innovation in AI.

What You'll Do

1. Build production-grade CV models for industrial use cases — defect detection, safety compliance, worker behavior analysis, object tracking, and process anomaly detection.
2. Deploy algorithms across multiple form factors — static industrial cameras, autonomous inspection robots, and drones — with on-device real-time inferencing.
3. Optimize models for edge hardware using TensorRT, ONNX Runtime, OpenVINO, and NVIDIA Jetson/DeepStream.
4. Design feedback loops — data flywheels, model drift monitoring, active learning pipelines — to continuously improve post-deployment performance.
5. Conduct site visits at industrial facilities. Understand the real environment — lighting, occlusions, safety constraints, operational rhythms — before designing a solution.
6. Translate operator-level problems into ML problem formulations and present results to both technical and non-technical client stakeholders.

Tech Stack

1. Core CV/ML: PyTorch, OpenCV, Ultralytics YOLO, MMDetection, Detectron2, Albumentations
2. Edge Inference: TensorRT, ONNX Runtime, OpenVINO, NVIDIA Jetson, DeepStream SDK, NVIDIA Triton
3. Cloud (Azure): Azure ML, Azure IoT Hub/Edge, Azure Container Registry, Azure Monitor
4. MLOps: Label Studio / CVAT / Roboflow, MLflow, DVC, FastAPI, Docker

Must Have

1. 3–5 years of hands-on experience building and deploying CV models to production
2. Prior experience in at least one industrial domain: manufacturing quality inspection, workplace safety monitoring, asset tracking, or process automation
3. Experience conducting site visits and designing solutions around real operational constraints
4. Proficiency with on-device inference optimization (TensorRT, ONNX, or equivalent)
5. Strong Python fundamentals with production coding standards

Good to Have

1. Experience deploying on NVIDIA Jetson or similar edge hardware
2. Familiarity with Azure IoT Edge and Azure ML pipeline
3. Exposure to drone/UAV-based CV deployments or robotic inspection systems
4. Understanding of camera calibration or 3D vision
5. Active learning / human-in-the-loop annotation pipeline experience

Why Valiance

✔ Your models run in the field — on factory floors, not in demos

✔ Direct client engagement means faster feedback and more interesting problems

✔ Work alongside 150+ engineers on projects that span industries and government

✔ Strong career growth in a recognized, award-winning deeptech firm