AI Research Intern at Origin

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

07 Jun, 26

Salary

0.0

Posted On

09 Mar, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Generative Models, Multimodal Learning, Diffusion Models, Vision-Language Architectures, VLM, VLA, Data Annotation, PyTorch, JAX, Deep Learning, Probabilistic Modeling, Computer Vision, Contrastive Pre-training, Active Learning, Self-Training, Git

Industry

Robotics Engineering

Description

About Origin Origin (previously 10xConstruction) is building general-purpose autonomous robots for US construction to tackle rising costs, safety risks, and labor 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 an AI Research Intern you'll push the frontiers of generative and multimodal learning that power our autonomous robots. You will prototype diffusion-based vision models, vision–language architectures (VLAs/VLMs) and automated data-annotation pipelines that turn raw site footage into training gold. Key Responsibilities Design and train diffusion-based generative models for realistic, high-resolution synthetic data. Build compact Vision–Language Models (VLMs) to caption, query and retrieve job-site scenes for downstream perception tasks. Develop Vision–Language Action Models (VLA) objectives that link textual work-orders with pixel-level segmentation masks. Architect large-scale auto-annotation pipelines that transform unlabeled images / point-clouds into high-quality labels with minimal human input. Benchmark model performance on accuracy, latency and memory for deployment on Jetson-class hardware; compress with distillation or LoRA. Collaborate with perception and robotics teams to integrate research prototypes into live ROS 2 stacks. Qualifications & Skills Strong foundation in deep learning, probabilistic modeling and computer vision (coursework or research projects). Hands-on experience with diffusion models (e.g., DDPM, Latent Diffusion) in PyTorch or JAX. Familiarity with multimodal transformers / VLMs (CLIP, BLIP, Flamingo, LLaVA, etc.) and contrastive pre-training objectives. Working knowledge of data-centric AI: active learning, self-training, pseudo-labeling and large-scale annotation pipelines. Solid coding skills in Python, PyTorch / Lightning, plus git-driven workflows; bonus for C++ and CUDA kernels. Bonus: experience with on-device inference (TensorRT, ONNX Runtime) & synthetic data tools (Isaac Sim). Preferred Experiences PyTorch or JAX C++ CUDA kernels ONNX Runtime TensorRT Isaac Sim Latent Diffusion

Responsibilities

The intern will design and train diffusion-based generative models for synthetic data and build compact Vision-Language Models (VLMs) for scene captioning and querying. Key tasks also involve developing Vision-Language Action Models (VLA) objectives and architecting large-scale auto-annotation pipelines.