AI Research Engineer

Location: Bengaluru | Work Mode: On-site | Employment: Full-time

Role Overview

We are looking for an AI Research Engineer to work on advanced Computer Vision, Generative AI, Vision-Language Models (VLMs), and Vision-Language-Action (VLA) systems for autonomous robotics.

The role combines AI research with production engineering taking ideas from research and experimentation through evaluation, optimization, and deployment on real-world robotic systems.

Key Responsibilities

• Research and develop Diffusion-based Generative AI models for synthetic data generation, defect simulation, photorealistic environments, and domain adaptation.
  
• Design and train VLMs/VLAs connecting text instructions, visual data, CAD/spatial information, and sensor inputs for scene understanding and intelligent decision-making.
  
• Build scalable auto-annotation and data-centric AI pipelines using Active Learning, Self-Training, Pseudo-Labeling, Weak Supervision, and Synthetic Data.
  
• Develop AI workflows capable of handling millions of images, video frames, and point clouds with minimal manual annotation.
  
• Optimize models for edge deployment using INT8 quantization, LoRA, Knowledge Distillation, TensorRT, ONNX Runtime, CUDA, and C++.
  
• Work with NVIDIA Jetson-class edge hardware and integrate AI models with robotics systems.
  
• Own the complete research lifecycle: problem definition → literature review → prototyping → training → evaluation → optimization → production handoff.
  
• Collaborate with Computer Vision, Perception, Robotics, and Controls teams.
  
• Contribute to technical documentation, research publications, and mentor junior engineers/interns.
  

Requirements

Must-Have Skills & Experience

• 3 to 7 years in Deep Learning, AI Research, Computer Vision, or related R&D; M.S./Ph.D. in CS, EE, Robotics, or related fields is highly relevant.
  
• Strong hands-on experience with Diffusion Models: DDPM, LDM, ControlNet, Generative Modeling, Synthetic Data, or Domain Adaptation.
  
• Strong experience with VLMs / Multimodal Transformers, such as CLIP, BLIP-2, LLaVA, Flamingo, or equivalent architectures.
  
• Proven experience with Active Learning, Pseudo-Labeling, Self-Training, Weak Supervision, and automated annotation.
  
• Advanced Python + PyTorch skills; JAX is a plus.
  
• Experience with scalable training frameworks such as PyTorch Lightning, DeepSpeed, Ray, or equivalent.
  
• Strong understanding of Probability, Optimization, Linear Algebra, and Information Theory.
  
• Ability to translate research concepts into production-ready AI systems.
  

Good to Have

• Robotics / Autonomous Systems / Embodied AI / Perception
  
• ROS 2, Isaac Sim, Open3D, Nav2, MoveIt 2
  
• 3D Computer Vision / Point Clouds
  
• TensorRT / ONNX Runtime / CUDA / C++
  
• Experience deploying models on NVIDIA Jetson or edge AI devices
  
• Strong research publications in AI/ML, Computer Vision, Generative AI, or Robotics.