AI Research Engineer

Origin Control Solutions Ltd; Bengaluru; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Origin Control Solutions Ltd in Bengaluru is seeking a senior AI Researcher to translate cutting-edge diffusion and vision-language advances into robust real-time robotics software for construction sites.

You will lead design and training of VLMs/VLA models, architect scalable data pipelines, and optimize models for edge devices while mentoring interns and publishing insights at conferences and internal reports.

Qualifications

• 3+ years in deep-learning R&D or Ph.D./M.S. in CS, EE, Robotics or related field with strong publication record.
• Demonstrated expertise in diffusion models (DDPM, LDM, ControlNet) and multimodal transformers / VLMs (CLIP, BLIP-2, LLaVA, Flamingo).
• Proven success building large-scale data-centric AI workflows—active learning, pseudo-labeling, weak supervision.
• Advanced Python, PyTorch (or JAX), experiment tracking and scalable training (PyTorch Lightning, DeepSpeed, Ray).
• Familiarity with edge-AI runtimes (TensorRT, ONNX Runtime), and CUDA / C++ performance tuning.
• Strong mathematical foundation (probability, information theory, optimization) and ability to translate theory into production code.
• Bonus: experience with synthetic data generation in Isaac Sim or robotics perception stacks (ROS2, Nav2, MoveIt 2, Open3D)

Responsibilities

• Research & innovate diffusion-based generative models for photorealistic wall-surface simulation, defect synthesis and domain adaptation.
• Architect and train Vision-Language Models (VLMs) and Vision-Language Action Models (VLA) objectives that connect textual work orders, CAD plans and sensor data to pixel-level understanding.
• Lead development of auto-annotation pipelines (active learning, self-training, synthetic data) that scale to millions of frames and point-clouds with minimal human effort.
• Optimize and compress models (INT8, LoRA, distillation) for deployment on Jetson-class edge devices under ROS 2.
• Own the full lifecycle—problem definition, literature review, prototyping, offline/online evaluation and production hand-off to perception & controls teams.
• Publish internal tech reports and external conference papers; mentor interns and junior engineers.

Skills

Deep learning R&D

Diffusion models

Multimodal transformers

Python & PyTorch

Experiment tracking

Edge AI platforms

CUDA & C++ optimization

Publications track record

Education

PhD in CS/EE/Robotics

MS in CS/EE/Robotics

Tools

PyTorch

JAX

PyTorch Lightning

DeepSpeed

Ray

TensorRT

ONNX Runtime

CUDA

C++

Job description

About Origin

Origin (previously 10xConstruction) is building general-purpose autonomous robots for US construction to tackle rising costs, safety risks, and labour shortages. Our modular, multi-trade platform combines purpose-built hardware with real-time site intelligence to navigate complex environments and execute tasks with precision. Trained in high-fidelity simulation and already deployed on live sites, our robots deliver 5x faster execution, 250%+ margin expansion, and significant cost savings. Join India’s most talent-dense robotics team consisting of individuals from IITs, Stanford, UCLA, etc.

About the Role

As a core member of the AI Research team you'll turn cutting-edge, vision-language and diffusion advances into robust real-time systems that see reason and act on dynamic construction sites.

Key Responsibilities

• Research & innovate diffusion-based generative models for photorealistic wall-surface simulation, defect synthesis and domain adaptation.
• Architect and train Vision-Language Models (VLMs) and Vision-Language Action Models (VLA) objectives that connect textual work orders, CAD plans and sensor data to pixel-level understanding.
• Lead development of auto-annotation pipelines (active learning, self-training, synthetic data) that scale to millions of frames and point-clouds with minimal human effort.
• Optimize and compress models (INT8, LoRA, distillation) for deployment on Jetson-class edge devices under ROS 2.
• Own the full lifecycle—problem definition, literature review, prototyping, offline/online evaluation and production hand-off to perception & controls teams.
• Publish internal tech reports and external conference papers; mentor interns and junior engineers.

Qualifications & Skills

• 3+ years in deep-learning R&D or Ph.D./M.S. in CS, EE, Robotics or related field with strong publication record.
• Demonstrated expertise in diffusion models (DDPM, LDM, ControlNet) and multimodal transformers / VLMs (CLIP, BLIP-2, LLaVA, Flamingo).
• Proven success building large-scale data-centric AI workflows—active learning, pseudo-labeling, weak supervision.
• Advanced proficiency in Python, PyTorch (or JAX), experiment tracking and scalable training (PyTorch Lightning, DeepSpeed, Ray).
• Familiarity with edge-AI runtimes (TensorRT, ONNX Runtime), and CUDA / C++ performance tuning.
• Strong mathematical foundation (probability, information theory, optimization) and ability to translate theory into production code.
• Bonus: experience with synthetic data generation in Isaac Sim or robotics perception stacks (ROS2, Nav2, MoveIt 2, Open3D)