Senior AI Engineer (Computer Vision) - Python, PyTorch, OpenCV | upto 50 LPA | Mumbai, Bangalore | Immediate Joiner

Hiring for

An exciting InsurTech startup building an AI-native stack for the Insurance.

Role

Senior AI Engineer (Computer Vision) - Python, PyTorch, OpenCV - Immediate Joiner

Positions

1

Experience

4 to 6 years

Location(s)

Bangalore, Mumbai

Type

On-site / Permanent

Salary

Up to INR 50 LPA (Includes 10-20% Variable)

Notice Period

Immediate to 15 days

About the role

Seeking a Senior Computer Vision Engineer to design, develop, and deploy state-of-the-art vision and AI systems for real-world applications. The ideal candidate combines deep expertise in computer vision, machine learning, and software engineering with experience delivering production-scale solutions.

Key Responsibilities

• Architect and develop computer vision and video analytics solutions.
• Build and optimize models for object detection, segmentation, tracking, OCR, pose estimation, and anomaly detection.
• Deploy AI models to cloud, edge, and embedded platforms.
• Lead technical design and code reviews.
• Drive research-to-production adoption of the latest vision technologies.
• Build maintainable and scalable ML services and APIs.
• Optimize models and inference pipelines for latency, throughput, and memory efficiency.
• Design solutions that can handle real-world edge cases and operate reliably at scale.

Required Skills

• 5+ years of experience in Computer Vision, Machine Learning, or AI Engineering.
• Expert-level proficiency in Python, PyTorch, OpenCV, and deep learning.
• Strong experience with:

-Object Detection

-Segmentation

-Multi-Object Tracking

-Video Analytics

-Image Processing

-Camera Geometry

• Experience with:
• Video analytics and temporal modelling
• Tracking at scale
• Experience deploying and maintaining production-grade computer vision systems.
• Strong understanding of real-world computer vision challenges.
• Good understanding of:
• Vision Transformers (ViTs)
• Multimodal and Vision-Language Models (VLMs)

Good to have

• Docker
• MLOps
• ONNX
• TensorRT
• NVIDIA GPUs
• AWS, Azure, or GCP
• Browser-based deployment
• Quantization techniques
• GPU profiling and performance optimization