Senior Deep Learning Engineer

BACKGROUND Rebar is building the next-generation operating system for commercial HVAC, electrical, and plumbing suppliers and subcontractors. Over the past year, our V1 quoting product has scaled to thousands of quotes completed weekly, doubled revenue in 2026, and gained adoption across many of the top suppliers in North America. Fresh off a $14M Series A backed by leading construction tech investors, we're entering our next phase of growth — with AI at the center of everything we build next. We’re looking for a Senior Deep Learning Engineer with extensive experience in modern neural network techniques and PyTorch to help us push the boundaries of computer vision in real-world environments. You’ll be joining a small, highly capable team focused on delivering practical, production-ready ML systems — from data pipelines through to fine-tuned models — in a fast-moving startup context. This role is ideal for someone who enjoys working with models under the hood, building and adapting training workflows, and applying research ideas to novel engineering challenges. Our work involves more than model inference — we design training workflows, develop evaluation pipelines, and engineer solutions that go beyond standard model usage. RESPONSIBILITIES - Model Training & Development: Design and train deep learning models for layout analysis, OCR, object detection, image to graph, and other related tasks. In some cases, you’ll extend or adapt existing architectures; in others, you’ll help design custom approaches from the ground up. - Evaluation and Monitoring: Build robust metrics, monitor production model performance, and proactively identify failure modes and areas for improvement. - Collaboration and Integration: Work closely with the engineering team to integrate models into our product and infrastructure. Participate in architecture and roadmap decisions. WHAT WE’RE LOOKING FOR You should feel confident implementing training logic, experimenting with model internals, and debugging the kinds of real-world issues that arise when pushing ML into production. We’re seeking someone with deep learning mastery and enjoys turning ideas into working, production-ready systems. This role is a great fit if you enjoy getting deep into PyTorch, working across the full ML stack, and solving open-ended modeling problems. REQUIRED QUALIFICATIONS - Master's degree or PhD in Computer Science, Electrical Engineering, or other relevant field with main focus on deep learning. - Proven ability to implement and adapt techniques or architectures from academic or industry literature. - Proven track record tackling novel ML challenges in the field of Deep Learning. - 3+ years of experience developing and adapting model architectures with PyTorch. - 2+ years of experience with deep learning for computer vision applications, especially semantic segmentation or object detection. - 2+ years of experience with production-level code development and optimization. NICE TO HAVE - Experience with active learning setups - Applied experience with RLHF (Reinforcement Learning from Human Feedback) - Published research developing SOTA computer vision or (or other DL) models - Experience with deployment and monitoring pipelines for ML systems. COMPENSATION AND BENEFITS - Salary: Competitive - Equity: Meaningful equity package, commensurate with experience - Benefits: Comprehensive medical, dental, and vision coverage - Perks: Free lunches and dinners provided This is a salaried, onsite role located in New York City's beautiful Flatiron district, just minutes away from Madison Square Park and Union Square. Working onsite offers invaluable opportunities for real-time collaboration, creative problem-solving, and building strong connections within our talented and dynamic team. You'll be at the heart of our fast-paced operations, actively contributing to a culture that values engagement, growth, and teamwork.