AI Engineer Computer Vision

Hiring: AI Engineer – Computer Vision | 2-3 Years Exp | On-site: Andhra Pradesh, India

Are you looking to apply deep learning and vision systems where they make an immediate, real-world impact on industrial sustainability and worker safety

At V-OptimAIse, we deploy advanced AI and machine learning to cut the carbon footprint and boost operational reliability in steel manufacturing. We build real-time predictive and diagnostic systems that identify bottlenecks, catch critical surface/product anomalies, and monitor human safety to prevent catastrophic incidents.

We are looking for an AI Engineer – Computer Vision with 2-3 years of full-time experience to develop, optimize, and deploy highly efficient vision pipelines directly into our industrial manufacturing environments.

What You Will Do

Architect, train, and optimize deep learning models for real-time object detection, anomaly detection, defect classification, and segmentation.

Build and deploy specialized vision pipelines for industrial PPE compliance and human safety monitoring on the factory floor.

Optimize models for very low latency and maximum FPS, executing edge deployments in high-temperature, harsh industrial settings.

Manage end-to-end dataset pipelines, including curation and labeling workflows using tools like CVAT.

Integrate computer vision inference pipelines with back-end application services and monitoring dashboards.

Collaborate closely with data scientists, software engineers, and domain specialists to validate and iterate on model accuracy in real-world conditions.

What You Bring (Required)

2 to 3 years of full-time, hands-on experience in Computer Vision and Deep Learning.

Deep proficiency in Python and C/C++ for performance-critical vision applications.

Extensive experience with model architectures, specifically Vision Transformers (ViT), Vision-Language Models (VLM), and advanced detection/segmentation models (e.g., YOLO variants, Mask R-CNN).

Practical experience taking models beyond notebooks: quantization, pruning, and deploying to production environments (e.g., TensorRT, ONNX Runtime).

A strong understanding of GPU architecture (e.g., CUDA, memory management, parallel processing) to extract maximum performance and optimize inference speeds.

Hands-on experience developing vision systems for industrial PPE and human safety monitoring.

Strong grounding in computer vision fundamentals, image preprocessing, and managing annotation workflows via CVAT.

Desirable & Bonus Points

B.E. in Computer Science, Artificial Intelligence, or a related discipline.

Experience with Edge AI deployments on embedded hardware (e.g., NVIDIA Jetson, industrial IPCs).

Familiarity with streaming protocols (RTSP, WebRTC) and multi-camera pipeline orchestration.

Compensation & Terms

CTC: 4 LPA (Including Bonus)

Training: 3-month training period

Probation: 6-month probation period

Location: On-site – Andhra Pradesh, India

Employment Type: Full-Time

Apply: Send your resume and portfolio/GitHub to [Confidential Information]

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