Founding Computer Vision Applied Scientist

Role:
Founding Computer Vision Applied Scientist

Location:
New York (4 days in office)

Salary: $150k–$200k base salary + equity

The Opportunity

We’re looking for a Founding Applied Scientist to build enterprise-grade AI from day one as our platform scales from single locations to large, multi-site deployments. You’ll own the entire model lifecycle - from data strategy and quality checks to training, inference optimization & translating results into clear insights for engineers and execs.

This is a hands-on, production-focused role. You’ll write real code, ship real models, and solve real-world problems in computer vision - not publish papers. You’ll collaborate closely with a high-caliber, distributed engineering team while working from NYC (4 days/week in office). You’ll report directly to the CTO and play a key role in shaping both technical direction and execution.

You’ll join a venture-backed company at a pivotal stage, with the chance to influence architecture, research direction, and production systems that operate in the real world. Plus, you'll be making a positive difference in society.

What you’ll do

• Design, train, and deploy computer vision models for large-scale production use
• Own data collection strategy, labeling quality, and performance evaluation
• Optimize models for real-time inference and reliability
• Work closely with engineering to ship customer-facing AI features
• Communicate technical tradeoffs and results to technical and non-technical stakeholders

What we’re looking for

Experience

• 3+ years in applied ML, computer vision, or ML engineering roles
• Proven experience shipping production computer vision systems (e.g., YOLO-style architectures or similar)
• Comfortable collaborating with distributed teams across time zones
• Track record of delivering customer-facing ML features end-to-end

Education

• MS or PhD in Computer Science, Machine Learning, Computer Vision, or related field (desirable)

Technical skills

• Advanced Python with PyTorch or Tensor Flow
• Deep experience across the full ML lifecycle: training, optimization, deployment, and monitoring
• Strong production coding skills and system-level thinking

Not a fit if

• Your background is purely academic or research-only
• You can’t point to recent, hands-on production code

Compensation

• Founding-team equity
• High ownership, high impact, and real influence on the product and technology