AI Research Engineer

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 Alignment (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)
  

Why join us?

• Own breakthrough tech from idea to autonomous robot on active job-sites—your work leaves the lab fast
• Collaborate cross-functionally with perception, controls, and product teams & publish at top venues with company support
• Shape an industry by replacing dangerous, repetitive construction labor with intelligent robots
• Competitive salary + equity, hardware budget, flexible hybrid work, and a culture that prizes deep work and rapid iteration
  

Requirements

• Vision-Language Models
• Vision-Language Alignment
• R\&D
• Ph.D./M.S. in CS, EE, Robotics
• TensorRT,
• ONNX Runtime
• CUDA / C++