Technical Lead (Machine Learning)

Lead a pioneering start up at the forefront of quantum mechanics and AI. We’re building break through novel ML models that redefine what’s possible. Backed by top-tier investors, we rank among the top 1% of Series A start ups globally, offering a rare opportunity to shape the future of AI.

We’re looking for a Technical Lead (ML) to play a pivotal role in our next phase of growth- scaling a world-class engineering team, building high-performance infrastructure, and helping lead the transformation of cutting-edge research into scalable, revenue-generating ML products.

What We Offer

Up to $325,000 base + Bonus

Equity in a rapidly growing AI start up

Hybrid working 3 days onsite per week in NYC

Your Role

You’ll drive the evolution from research-driven prototypes to scalable, production-ready ML systems—emphasising performance, tooling, and cross-functional execution

Frontline manager with a hand in the day to day operations – can jump into code if needed

Define and execute the engineering roadmap in alignment with company strategy and research advancements

Foster a culture of technical excellence, collaboration, and continuous learning

Develop and maintain scalable, high-performance infrastructure for ML research and deployment

Optimise distributed systems, GPU acceleration (CUDA), and parallel processing for large-scale training

Design and implement robust ML tooling and automation pipelines.

Support client deployment workflows, integration pipelines, and long-term infrastructure needs.

Champion best practices in DevOps, CI/CD & infrastructure automation.

Ensure systems are scalable, modular, well-documented, and reliable.

Evaluate and integrate emerging technologies to improve compute efficiency and infrastructure scalability.

Requirements

10+ years of experience, including some in a leadership capacity

Can you jump into code if needed?

Deep expertise in ML infrastructure, ML frameworks, distributed computing frameworks, Python (& others)

Strong grasp of DevOps practices, including CI/CD, orchestration and containerization (Kubernetes & Docker)

Proven ability to lead, mentor, and grow high-performing engineering teams

Exceptional communication and cross-functional leadership skills, with experience collaborating across research, engineering, and business units.

Bonus

Helped scale ML-first start up from early-stage prototypes to production-grade systems

Quantum mechanics or complex linear algebra and statistics

Expertise in high-performance computing (HPC), including CUDA, GPU programming, and parallel computing architectures

ML applications in finance, healthcare, or chemistry

Ready to Shape the Future?