AI Research Engineer
Summary
Research and deploy advanced AI models (Diffusion, VLMs, VLAs) for autonomous robotics, optimizing for edge deployment and scaling data pipelines.
This role is for one of the Weekday's clients
Salary range: Rs 1500000 - Rs 3000000 (ie INR 15 - 30 LPA)
Min Experience: 3+ years
Location: Bangalore, Karnataka
JobType: full-time
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.
This is a research-focused AI role working on Computer Vision, Generative AI, and multimodal models for autonomous systems. The role involves developing Diffusion Models, VLMs, and data-centric AI solutions to improve machine perception and understanding, while taking research models through experimentation, optimization, and deployment on real-world edge systems.
Requirements
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:
- 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.
Must-have skills
Computer Vision, Diffusion Models, AI Research
Good-to-have skills
Python, Pytorch, Vision Language Model
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