Role: Lead AI Engineer

Function: AI/Machine Learning Engineering

Location: Not specified

Type: Full-time

Compensation: Competitive compensation package with equity

Industry: Construction Technology, Robotics, AI/Machine Learning

About Company

The company builds general-purpose autonomous robots for US construction. The robots tackle rising costs, safety risks, and labor shortages.

The team consists of 140 robotics, AI, and hardware experts from top institutions. The company is well-funded and already deploying robots on live job sites.

Position Overview

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. You'll lead research and development of next-generation AI models for autonomous construction robotics.

Role & Responsibilities

• Research and 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) that connect textual work orders, CAD plans and sensor data to pixel-level understanding
• Lead development of auto-annotation pipelines using active learning, self-training, and synthetic data that scale to millions of frames and point-clouds
• Optimize and compress models (INT8, LoRA, distillation) for deployment on Jetson-class edge devices under ROS 2
• Own the full AI research lifecycle from problem definition and literature review to prototyping, evaluation and production hand-off
• Publish internal tech reports and external conference papers while mentoring interns and junior engineers
• Collaborate with perception and controls teams to integrate research breakthroughs into production robotics systems

Must Have Criteria

• 8+ years in deep learning R&D or Ph.D./M.S. in Computer Science, Electrical Engineering, Robotics or related field
• Strong publication record in top-tier AI/ML conferences (NeurIPS, ICML, ICLR, CVPR, ICCV)
• Demonstrated expertise in diffusion models (DDPM, LDM, ControlNet) with hands-on implementation experience
• Proven experience with multimodal transformers and Vision-Language Models (CLIP, BLIP-2, LLaVA, Flamingo)
• Advanced proficiency in Python and PyTorch with experience in scalable training frameworks (PyTorch Lightning, DeepSpeed)
• Experience working with large-scale computer vision datasets (millions of images, terabytes of visual data)
• Proven success building large-scale data-centric AI workflows including active learning and pseudo-labeling

Nice to Have

• Experience with computer vision in construction, manufacturing, or industrial environments
• Experience with synthetic data generation in Isaac Sim or similar robotics simulation environments
• Familiarity with edge-AI runtimes (TensorRT, ONNX Runtime) and CUDA/C++ performance optimization
• Experience with robotics perception stacks (ROS2, Nav2, MoveIt 2, Open3D)
• Experience with JAX framework and distributed training on large GPU clusters

What We Offer

• Opportunity to work on cutting-edge AI research with real-world impact in construction automation
• Collaborate with a world-class team from IITs, Stanford, UCLA and other top institutions
• Access to state-of-the-art computing resources and robotics hardware for research
• Competitive compensation package with equity in a well-funded early-stage startup
• Direct impact on transforming a $1.8 trillion construction industry through autonomous robotics