Associate Principal Lead- Computer Vision Specialist

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.