Associate Principal Lead- Computer Vision Specialist

Tiger Analytics; Hyderabad, Chennai District, Bengaluru; Hybrid; INR 2,500,000 - 3,800,000; Full time

Job summary

Tiger Analytics seeks a Senior/Lead Computer Vision Specialist to design, deploy, and operationalize vision models for cloud and edge deployments. You will shape end-to-end CV pipelines, collaborate with cross-functional teams, and drive scalable AI solutions across industries.

The role emphasizes production-ready ML workflows, model optimization, and hands-on experience with CNNs, VLMs, OpenCV, and Python development in a fast-paced consulting environment.

Qualifications

• 5-9 years of professional experience in Computer Vision, MLE, and MLOps.
• Strong experience with DL frameworks and CV libraries.
• Experience with deployment across cloud and edge environments.

Responsibilities

• Design, develop, and deploy scalable computer vision solutions.
• Build production-ready pipelines for training and evaluation.
• Optimize models for edge and cloud performance.
• Collaborate with cross-functional teams and clients to integrate CV solutions.

Job description

Role & responsibilities

As a Senior/Lead Computer Vision Specialist, you will be at the forefront of AI innovation focusing on visual intelligence. Your role will involve designing, deploying, and operationalizing sophisticated vision modelsranging from Convolutional Neural Networks (CNNs) to Vision-Language Models (VLMs)to solve complex business problems. You will work closely with cross-functional teams to create scalable, production-ready Computer Vision solutions deployed across both cloud architectures and edge devices, driving intelligent automation and insights across industries.

What do we expect?

• Computer Vision & Deep Learning: Design, develop, deploy, and scale advanced applications using Convolutional Neural Networks (CNNs) targeted for both robust cloud architectures and constrained edge environments.
• Image Processing: Leverage OpenCV and traditional image processing techniques alongside modern deep learning approaches to build robust, end-to-end visual pipelines.
• Model Optimization & Quantization: Apply model quantization, pruning, and optimization techniques to ensure efficient inference and low-latency performance on edge devices.
• ML Training & Evaluation Pipelines: Design, build, and maintain scalable ML training and evaluation pipelines to handle large volumes of image and video data consistently.
• Model Serving at Scale: Implement highly scalable model inference using industry-standard model servers such as Ray Serve, NVIDIA Triton Inference Server, or similar technologies.
• Vision-Language Models (VLM): Utilize hands-on experience working with Vision-Language Models (VLM) for multi-modal tasks, visual Q&A, and advanced visual understanding.
• Software Engineering & Development: Utilize strong Python development experience to build end-to-end MLOps solutions. C++ development experience is good to have for performance-critical vision algorithms.
• Client Engagement & Collaboration: Partner with Consulting, Engineering, and Platform teams to integrate CV solutions into broader architectures, and work directly with clients to tailor AI solutions.

Preferred candidate profile

Overall 5-9 years of professional experience with real-world, hands-on exposure to Computer Vision, Machine Learning Engineering (MLE), and MLOps.

• Extensive expertise in deep learning frameworks (PyTorch, TensorFlow) and computer vision libraries (OpenCV, PIL, scikit-image).
• Proven experience in building CV models that are scalable, reliable, and production-ready across varied deployments.
• Familiarity with containerization (Docker), orchestration (Kubernetes), model tracking (MLflow, Weights & Biases), and cloud platforms (AWS/GCP/Azure) for deploying AI solutions at scale.
• Strong communication skills with the ability to translate complex technical concepts into business-friendly insights and recommendations.