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 Machine Learning Engineering Manager 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 help 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
• Help 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.
• ML applications in finance, healthcare, Genomics or chemistry

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

Ready to Shape the Future?

If you're excited about leading a team that's redefining the machine learning paradigm and driving impact across multiple high-stakes industries, we’d love to hear from you - apply now!