Associate Principal - Data Sciences

Experience: 11–15 Years

Location: Bengaluru

Type: Permanent

Role Summary

We are seeking an experienced and innovative R&D Specialist with a strong background in Generative AI (GenAI) and complementary expertise in Computer Vision and Predictive Modeling in the Retail and Consumer space. The ideal candidate will drive the research, design, and prototyping of AI-based solutions that push the boundaries of industrial applications, digital twins, and autonomous systems.

Key Responsibilities

• Lead and contribute to applied research in Generative AI, including LLMs, Vision-Language Models (VLMs), Multimodal AI, and Prompt Engineering.
• Collaborate with product and engineering teams to translate GenAI research into real-world use cases for industries like manufacturing, automotive, oil & gas, and healthcare.
• Conduct R&D in Traditional AI domains such as:
• Computer Vision: object detection, segmentation, OCR
• Predictive Analytics: RUL, anomaly detection, forecasting
• Build and evaluate AI models using tools such as PyTorch, TensorFlow, Hugging Face, LangChain, OpenCV, Scikit-learn, etc.
• Publish internal white papers, IP disclosures, and present research outcomes to leadership and stakeholders.
  

• 7–12 years of hands-on experience in AI/ML R&D, including a minimum of 2–3 years in GenAI.
• Strong experience with LLMs: fine-tuning, model evaluation, vector databases, and inference pipelines.
• Deep expertise in at least one traditional domain:
• Computer Vision (e.g., CNNs, YOLO, Mask R-CNN) OR
• Predictive Modeling (e.g., time-series, survival models).
• Experience deploying models in Edge/Cloud/MLOps pipelines and working with enterprise data platforms.
• Strong programming skills in Python with experience in notebook-based prototyping, REST APIs, and ML libraries.
  

• Knowledge of Agentic AI, Digital Twins, or Simulation-based learning.
• Experience in industrial AI domains (e.g., smart factory, quality inspection, predictive maintenance).
• Exposure to generative vision models like Diffusion Models, GANs, or NeRFs.
• Experience collaborating in multidisciplinary R&D teams.
• Contributions to open-source, patents, or publications in AI/ML.
  
  

• Git
• Jenkins
• Kubernetes
• Cloud Computing
• Industrial AI – LLM
• Docker
• Generative AI / Open AI / Vector DB
• Industrial AI – LLM Ops
• Industrial AI – Machine Learning (ML)
• AR / VR / MR