Senior / Staff AI Engineer

New York, NY (Hybrid – 4 days/week in office)

Our client is an early-stage company revolutionizing development in America by streamlining collaboration between builders, developers, and local regulatory authorities. Their platform powers a private plan review solution used by some of the nation’s largest public retailers, developers, and home builders—helping projects move faster and stay within budget.

Backed by leading venture capital firms (including a recent ~$40M Series A), the team is combining deep expertise in technology and the built environment to reshape a multi-hundred-billion-dollar industry through automation and AI.

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The Opportunity

This role sits at the heart of our client’s AI engineering organization. They’re on a mission to automate one of the most costly and expertise-dependent bottlenecks in the built environment—construction plan review. You’ll operate with a founder-like mindset, helping define the long-term data and ML strategy and building the foundation for how AI models interact with complex real-world architectural and regulatory data.

It’s a high-impact role with ownership over model development, MLOps design, and experimentation across LLMs and computer vision.

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What You’ll Do

• Design, build, and deploy scalable ML systems for real-world plan review automation

• Collaborate with domain experts (architects, engineers, regulators) to define and validate ML use cases

• Work with rich proprietary datasets including jurisdictional building codes, annotated plan reviews, and structured construction documents

• Own technical decision-making for data and ML infrastructure in partnership with the data engineering team

• Build and optimize pipelines for data processing, model training, and deployment

• Develop greenfield pre-training and fine-tuning pipelines for domain-specific LLMs and CV models

• Contribute to RLHF and retrieval workflows to inject domain expertise into model performance

• Evaluate, experiment with, and integrate new research in LLMs, CV, and multimodal systems

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You Might Be a Fit If You

• Have a graduate degree or equivalent experience in Computer Science, Data Science, or Machine Learning

• Bring 3+ years of experience shipping ML systems into production (not just research)

• Have experience with LLMs, AI agents, or MLOps in production environments

• Can translate open-ended product challenges into actionable, measurable ML solutions

• Stay current with the latest NLP/CV research and have a track record of experimentation or contribution

• Are excited by messy, real-world data—turning unstructured regulatory and architectural inputs into structured signals

• Thrive in startup environments where ownership and speed matter

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What Success Looks Like

90 days: A reproducible model pipeline and clear ML roadmap aligned with product + domain experts
6 months: Alpha model running in shadow mode via automated pipelines, showing >20% lift on real plans
12 months: Model in customer beta, cutting manual review time by 25%+ with scalable auto-retraining and monitoring

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Why Join

• Help design the data and model foundation for one of the most underexplored AI applications

• Work directly with experts across architecture, engineering, and regulatory domains

• Join an experienced, well-capitalized team backed by top-tier VCs

• Build AI that delivers measurable impact on real-world infrastructure and sustainability

Benefits include: Competitive salary ($215-255k base) and equity, performance-based bonuses, 100% medical coverage under the HDHP plan, 401(k), parental leave, wellness stipend, weekly catered lunches, team offsites, and a flexible hybrid environment (4 days in-office, 3 in summer).

Research indicates that men will apply to a role when they only meet 50-60% of the descriptions, however, when looking at women and other minority groups, they can look for up to a 99% match in order to apply to a role. If you feel you are a fit for our role, please still apply, don’t worry if you don’t tick every single box. We’d still love to hear from you. We encourage underrepresented talent to apply to all our roles & support accessibility needs.