Data Scientist- Computer Vision

Addenda

India

On-site

INR 4,200,000 - 6,500,000

Full time

11 hours ago
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Job summary

Addenda is seeking a Senior Data Scientist specializing in Computer Vision to design, develop, and deploy scalable vision-based AI systems. The role emphasizes traditional CV, feature engineering, and modern deep learning, with hands-on work on Agentic AI for autonomous decision-making.

You will lead production-ready vision solutions, collaborate with engineering, product, and business teams, and mentor peers while driving innovation across AI-powered products.

Qualifications

  • 6-8 years in Data Science / Computer Vision / AI roles with a B.Tech background.
  • Proven experience delivering production-grade vision systems.
  • Hands-on experience with model evaluation and optimization.

Responsibilities

  • Design and develop end-to-end computer vision pipelines for real-world applications.
  • Develop and optimize traditional computer vision algorithms and feature engineering.
  • Build and deploy deep learning models for instance and semantic segmentation.
  • Lead cross-functional collaboration across engineering, product, and business.
  • Mentor junior team members and contribute to architectural decisions.
  • Develop Agentic AI systems enabling autonomous reasoning and decision-making.
  • Optimize models for performance, scalability, and edge deployment.
  • Lead model evaluation, experimentation, and continuous improvement.

Skills

Traditional computer vision
Feature engineering
Deep learning for vision
Python

Tools

PyTorch
TensorFlow
OpenCV
ONNX

Job description

We are looking for a highly skilled Senior Data Scientist specializing in Computer Vision to lead the design, development, and deployment of advanced vision-based AI systems. The ideal candidate will have deep expertise in traditional computer vision, feature engineering, and modern deep learning techniques, along with hands-on experience in building Agentic AI systems for intelligent decision-making.

You will play a key role in building scalable, production-grade vision solutions and driving innovation across AI-powered products.

Key Responsibilities
  • Design and develop end-to-end computer vision pipelines for real-world applications.
  • Apply and optimize traditional computer vision algorithms:
  • Image processing, feature extraction, geometric transformations, tracking, and calibration
  • Perform advanced feature engineering:
  • Combine handcrafted features with deep learning embeddings
  • Improve model performance through feature selection and transformation techniques
  • Build and deploy deep learning models for:
  • Instance and Semantic Segmentation
  • Develop and integrate Agentic AI systems that:
  • Enable autonomous reasoning and decision-making
  • Integrate with external tools and APIs
  • Optimize models for performance, scalability, and edge deployment.
  • Lead model evaluation, experimentation, and continuous improvement.
  • Collaborate with cross-functional teams across engineering, product, and business.
  • Mentor junior team members and contribute to architectural decisions.
Required Skills & Qualifications
Experience
  • Experience: 6-8 Years (B.Tech), 4-6 Years (M.Tech) in Data Science / Computer Vision / AI roles
Core Technical Skills
  • Strong expertise in traditional computer vision:
  • Strong experience in feature engineering for vision tasks
  • Deep expertise in deep learning for vision:
  • Object Detection, Semantic Segmentation, and Instance Segmentation
  • Hands-on experience with:
  • PyTorch / TensorFlow / OpenCV / Onnx
  • Strong programming skills in Python
Agentic AI Expertise
  • Experience in designing Agent-based AI systems using LLMs
  • Familiarity with:
  • Tool usage, planning, memory, and orchestration frameworks
  • LangChain, AutoGen, or similar ecosystems
  • Ability to combine vision models with LLMs for intelligent workflows
Preferred Qualifications
  • Experience with Vision-Language Models (VLMs) and multimodal systems
  • Knowledge of MLOps / model lifecycle management (MLflow, Azure ML, etc.)
  • Experience in real-time or edge AI systems
  • Domain experience in:
  • Automotive, Insurance, Retail, Manufacturing, or Surveillance
  • Familiarity with cloud platforms (Azure, AWS, GCP)
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