AI Research Engineer
At a glance
Mid-level AI Research role at Origin. Bengaluru · full-time.
Pay not stated AI Research salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build diffusion models that simulate realistic wall surfaces, create defects and help models adapt across domains
- Train vision-language and vision-language-action models to connect work orders, CAD plans and sensor readings with image-level understanding
- Scale automatic labeling across large frame and point-cloud collections using active learning, self-training and synthetic examples
- Compress models for Jetson-class devices, then own their evaluation and production handoff to perception and controls teams
- Define research problems, review papers, test prototypes, assess results and write reports or conference papers while guiding junior engineers
What you bring
- At least three years in deep-learning research and development, or a relevant master's or Ph.D. with strong publications
- Hands-on depth with diffusion methods and multimodal vision-language transformer models
- Experience creating large-scale data workflows using methods such as active learning, pseudo-labeling or weak supervision
- Strong Python and PyTorch or JAX skills, plus advanced math and experience turning research into production code
Who this fits
This mid-level, full-time role is based onsite in Bengaluru. You’ll suit work that spans AI research, model deployment and collaboration with perception and controls teams, with some mentoring of interns and junior engineers.
From the employer
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)