Guthrie AI — Founding AI/ML Engineer

Guthrie AI — Founding AI/ML Engineer Type: Full-time | Hybrid (3 days/week onsite) | Washington, D.C. Compensation: $190,000–$200,000 + competitive equity Hiring count: 1 Visa sponsorship: Yes — H-1B Reports to: Chief AI Officer About Guthrie AI Guthrie AI is building the AI-powered workflow layer for construction — one of the world's largest industries and one that skipped the software era entirely. Subcontractors, their core customer, have seen no meaningful software innovation in 15+ years, and agents plus multimodal AI are the first real wedge in. Off-the-shelf models from OpenAI and Anthropic struggle with construction diagrams because those aren't in standard training data, which makes training in-house models a core technical bet. Founded: 2023 | Team size: ~11–50 (Seed stage; Chief AI Officer + 7 engineers — 2 AI/ML, 5 full-stack) | Total funding: Seed round just closed (term sheets signed, not yet announced); ~$2M ARR with a plan to 10x in 12 months Industry: Property Tech / Construction Tech / Agentic AI Website: guthrieai.com Office: Philadelphia, PA (newly opened hub; remote-first team) Why Candidates Should Join Own the model layer end-to-end: This is the founding AI/ML hire owning the entire model-development side of the platform and setting technical direction for the AI/ML team. A genuinely hard, defensible problem: Construction diagrams and floor plans aren't in any foundation model's training data, so you train in-house models — real CV depth, not API wrapping. Early-stage upside: Meaningful early-employee grant (ESOP pool), fresh seed round, ~$2M ARR with a credible 10x plan over the next 12 months. Intake Call Summary No intake call transcript was included on the role page. An intake video is present but not transcribed — update this section once the summary is available. The Role Guthrie is hiring a Founding AI/ML Engineer with deep computer vision expertise to own the model-development side of the platform and lead the in-house model work that off-the-shelf foundation models can't handle. What You'll Be Doing Train and improve in-house computer vision models for construction diagrams (segmentation, object detection, classifiers) Lead architectural and model-improvement work where off-the-shelf models hit their ceiling Own the model-development roadmap and set technical direction for the AI/ML team Build agentic orchestration and retrieval flows (RAG, fine-tuning, local vs foundation model decisions, cost optimization) Provide technical leadership and guidance to the 2–3 existing AI/ML engineers (who will report to this hire) Tech stack: Python, PyTorch, CUDA; CV (2D segmentation, object detection, classifiers; SAM / SAM3-tier foundation models); agentic orchestration & retrieval (LLMs, RAG, fine-tuning small language models, local vs foundation model trade-offs) Role split: ~half computer vision (the irreplaceable part), ~half agentic orchestration/retrieval (where "good enough" is acceptable if CV expertise is exceptional). Requirements Computer vision, 2D segmentation depth Python + PyTorch + CUDA Train in-house models (not just fine-tune) Construction diagrams / floor plans bonus East Coast, 3 days hybrid at Philly hub Green Flags 2D segmentation expertise with published work in floor plan localization, raster-to-sequence, structural priors, or comparable architectural CV. Direct domain match. Construction diagrams, floor plans, or technical drawings personal or professional exposure. Genuinely rare and high-signal. PyTorch + CUDA fluency with architectural model improvement track record (not just fine-tuning APIs) Research-trained but now hands-on. Agentic orchestration / retrieval experience as a secondary skill. Strong plus but not blocker. Red Flags TensorFlow-only background without PyTorch transition. PyTorch is the expected core framework; TensorFlow is dated for this work. Pure backend ML engineer without CV depth. Off-the-shelf model orchestrator without ability to train custom models. Pure research without willingness to ship. The role is hands-on technical leadership, not academic. Cannot do East Coast hybrid (3 days/week onsite). Flex only for genuinely exceptional candidates. Role Details Salary$190,000–$200,000EquityCompetitive — meaningful early-employee grant (ESOP pool); no % specifiedExperience6+ yearsOn-site policyEast Coast, 3 days/week onsite at Philly hub (flex for exceptional candidates)Visa sponsorshipH-1BEmployment typeFull-timeLocationWashington, D.C. Screening Questions None present on the role page — add here if Guthrie provides any. Interview Process Stage 1 — Initial Screen (30 min) — 30-minute hiring-manager screen. Stage 2 — Getting-To-Know-You Round — With Tuneer (Head of Product / co-founder), the Product team, and the CEO. Cultural and team fit. Stage 3 — ~2-hour Technical / Architecture Round — With Kaz and one of the other lead engineers. Architecture deep-dive and technical assessment. Stage 4 — Optional On-Site — At the Philly office (Amtrak-friendly from NY / DC). Not required, but a plus. Stage 5 — Offer Extended Stage 6 — Candidate Hired — Candidate accepts and starts. (Contrario's "Pending Approval" stage precedes Stage 1 as the platform approval gate.) Ideal Companies & Backgrounds No "Ideal Companies" section was present on the role page. Ideal Candidate Profiles For reference only — do not source these specific profiles. The role page labels this section "Ideal Candidates — DO NOT CONTACT." Hao Phung — LinkedIn link present on the page but the URL was not extractable from the HTML. Computer vision experience in floorplan reconstruction. The remaining four entries are reference research papers, not candidate profiles: "Waffle Research Paper," "Technical Drawing Research Paper," "Computer Vision Abstraction Research Paper," "3D Diffusion Research Paper" (each links to a paper/site, not a person). Rejected Candidate Feedback None present on the role page.