Tech Lead, Machine Learning (Applied AI)

Over 5 billion people use basic applications today, email, notes, tasks, calendar, and none of them are truly AI native. Our client's mission is to build proactive applications for anyone in the world, including people who aren't used to complex prompting. They've just raised $100 million and are bringing intelligence to conversations, errands, organizing, and workflows, with minimal to no prompting required.

The product is focused on achieving high reliability for long-running workflows, persistent context, and real-world task completion, with a strong belief that products should dramatically reduce hallucinations. The broader objective is to help anyone organize their life, so they can spend time on what's valuable and meaningful.

As Tech Lead, Machine Learning, you'll own the execution layer of the company's intelligence, turning research and model capabilities into reliable, scalable production systems. You'll work across the full model lifecycle, data, training, evaluation, inference, and deployment. This is a hands-on leadership role for someone who wants to operate at the intersection of research, systems, and product.

What You'll Own

• Own the end-to-end ML systems powering the company, from data and training through to evaluation, inference, and deployment
• Build and evolve training and fine-tuning pipelines for large models
• Design evaluation systems that measure capability, robustness, safety, and real-world product performance
• Architect high-performance inference systems, optimizing latency, GPU utilization, memory, cost, and reliability
• Build data pipelines and systems for high-quality real-world and synthetic training data
• Establish reliable production infrastructure for deploying, monitoring, and continuously improving models
• Partner closely with research and application engineering to turn model capabilities into product improvements
• Make pragmatic technical trade-offs and rapidly iterate based on real-world performance