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Cyvl

Head of AI

Posted Yesterday
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In-Office
Boston, MA, USA
300K-425K Annually
Senior level
In-Office
Boston, MA, USA
300K-425K Annually
Senior level
The Head of AI will lead AI/ML strategy, manage teams, and oversee the development of AI solutions for infrastructure mapping.
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About Us

Cyvl is a Boston-based tech startup revolutionizing how governments map and manage transportation infrastructure. Our enterprise-grade hardware and software solutions leverage 3D mapping sensors to capture LiDAR, imagery, and GPS data, retrofitted to our customers' vehicles. This data is processed through our AI-powered cloud pipelines to generate actionable geospatial insights that save cities time, money, and resources.

At Cyvl, our mission is to empower governments to build and maintain public infrastructure they're proud of. We are already accelerating decision-making nationwide through our sensors and Infrastructure Intelligence Platform. This role owns the AI/ML strategy that powers the next generation of our Intelligence Platform, translating a bold product vision into the technical roadmap, team, and systems that make it real.

We're a fast-moving, high-growth team that believes in solving real-world problems with authenticity, simplicity, and boldness. Every member of our team is empowered to take ownership, deliver results, and leave a lasting impact on the communities we serve.

About You

You've led AI/ML teams that built production systems on complex, multi-modal data. You've set technical strategy, hired engineers, and shipped products, not just published research. You're comfortable going hands-on with code and models when needed, but your real leverage is in figuring out what to build, in what order, and hiring the right people to build it. You've worked with sensor data, geospatial data, or physical-world AI, and you understand that the hardest problems aren't model architecture problems, they're data strategy problems. You want to build the AI function that teaches machines to understand physical infrastructure at a depth and scale that has never existed.

Key Responsibilities
  • Interpret Cyvl's Infrastructure Intelligence vision and translate it into a concrete AI/ML technical strategy covering perception (imagery + LiDAR), knowledge representation, and data architecture.

  • Be hands-on in the early months: set up the initial ML pipelines, make key architectural decisions, and validate technical approaches before you have a team.

  • Hire and lead the AI/ML team, starting with a senior ML engineer and a senior knowledge graph architect as the first two roles.

  • Own the full intelligence extraction pipeline: from raw sensor data to detections, geometric measurements, cross-modal representations, and a queryable knowledge graph.

  • Work directly with the CEO and engineering leadership to align AI/ML investments with product priorities and customer needs.

QualificationsRequired
  • 8+ years in ML/AI, with at least 3 years leading a team (hiring, managing, setting technical direction).

  • Track record of shipping production ML systems on sensor data, geospatial data, or multi-modal data at scale.

  • Experience setting AI/ML strategy for a product or business unit, not just executing someone else's roadmap.

  • Hands-on technical depth: you can train models, design data pipelines, and evaluate architectural tradeoffs yourself.

  • Experience with data-efficient learning approaches (active learning, semi-supervised methods, foundation model adaptation) in production.

  • Led teams of 3+ ML/AI engineers and made successful senior technical hires.

  • Strong communicator who can translate between technical AI/ML concepts and business/product strategy.

Nice to Have
  • Experience with LiDAR, point cloud data, or 3D perception.

  • Background in autonomous vehicles, HD mapping, satellite imagery, or infrastructure/civil engineering domains.

  • Experience building knowledge graphs or ontology-driven data architectures.

  • Familiarity with geospatial databases (PostGIS, spatial indexing).

  • Experience designing data architectures for agentic or LLM-driven access patterns.

  • Background at Palantir, an AV company, or a geospatial intelligence organization.

  • Experience at a startup or scaling an AI/ML function from zero.

What We Offer
  • Competitive salary and equity package ($300K-$400K total comp, equity-heavy)

  • Comprehensive health, dental, and vision coverage

  • 401(k) with immediate vesting

  • Generous PTO, paid parental leave, and flexible work options

  • Annual professional development stipend

  • Team events, referral bonuses, and a collaborative, growth-focused culture

  • Ownership of the entire AI/ML function at a company with real data, real customers, and a clear vision

About Cyvl

At Cyvl, you'll join a driven and supportive team that's all out in building technology with real impact. We care deeply about our work, our customers, and each other. Collaboration and trust are at the core of how we operate.

Our values guide how we operate and shape a team that is genuinely RAARE:

Real - authentic, transparent, focused on solving real problems with simple, effective solutions.

All Out - bold, driven, and committed to delivering results that matter.

Accelerating - always learning, growing, and moving with intention.

Reliable - we follow through and deliver at a consistently high bar.

Empowering - we lift each other up and help governments build infrastructure they can be proud of.

Learn How We Think

Learn about our startup journey

Learn what we are doing

Learn about our customers

Together, we stay curious, learn quickly, and keep raising the bar. If you want to grow, make an impact that truly matters, and be part of a team that's shaping the future of public infrastructure, you'll feel right at home at Cyvl.

At Cyvl, we welcome and celebrate diversity in all its forms. We do not discriminate based on race, color, religion, sex, gender identity or expression, sexual orientation, age, national origin, disability, veteran status, or any other protected characteristic. Your unique perspective is valued here.

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