Head of Applied AI

Director @ Kadence | AI & Machine Learning Talent Solutions

Head of Engineering / Applied AI

Reports to: Chief Creative Technologist

Company: Stealth AI Startup at the Intersection of Filmmaking & Advanced Machine Learning

We’re partnering with a stealth AI startup operating at the cutting edge of filmmaking and machine learning. Founded by a renowned, award‑winning creative leader in entertainment, the company has already delivered production‑grade AI tools used in major studio films generating hundreds of millions in box office revenue.

Backed by top‑tier media and technology investors, the company is preparing for rapid expansion—including a Series A raise and the buildout of its core engineering and applied AI teams. This is a rare opportunity to join early and shape the future of AI‑driven creativity.

The Head of Engineering & Applied AI will lead the engineering org responsible for building the company’s next‑generation generative AI products. This is not a research role—it's an engineering leadership role for someone with strong software engineering fundamentals who can architect robust systems guide high‑velocity execution, and partner closely with creative leaders to bring AI‑powered tooling to life.

You will oversee product engineering, applied AI integration, platform reliability, and team growth. You’ll collaborate directly with the Chief Creative Officer to translate creative vision into scalable technical systems used by filmmakers worldwide.

• Lead the process of integrating research models into production systems
  , including:
• Deployment strategies
• Roll‑out and iteration
• Monitoring, evaluation, and performance tracking
• Own production readiness and reliability of deployed ML models.

• Design and build end‑to‑end ML infrastructure and pipelines that:
• Interface closely with research teams
• Architect systems from zero to one
  , not just incremental improvements.
• Model optimization (latency, throughput, cost)
• Fine‑tuning and post‑training workflows
• Build and maintain data and training pipelines that directly support these efforts.

• Backend integrations with existing products and services
• Observability, logging, and feedback loops for deployed models
• Drive continuous improvement of deployed models through monitoring and iteration.

• Act as the applied AI lead between research and engineering.
• Provide technical leadership to ML engineers and partner closely with researchers.
• Set standards and best practices for production ML systems.

• Proven end‑to‑end ownership of shipping research ML models into production
  , including deployment, monitoring, iteration, and long‑term reliability in real‑world systems.
• Deep hands‑on expertise in applied ML infrastructure
  , including model serving, MLOps, production pipelines, and performance optimization in distributed, cloud‑based environments.
• Strong systems design capability
  , able to architect and whiteboard scalable ML systems and take platforms from zero to one and beyond.
• Senior technical leadership experience
  , with a track record of leading ML or platform engineering initiatives, mentoring engineers, and scaling high‑impact teams.
• Extensive production engineering background (8+ years) shipping complex, real‑time, or high‑traffic products, with a strong grasp of distributed systems and cloud architecture.
• Applied AI focus (not research‑only), with hands‑on experience integrating deep learning models into products and collaborating with research and creative stakeholders; experience with generative AI or computer vision strongly preferred.

Director

Full‑time

Engineering and Product Management

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