Staff Machine Learning Engineer

About This Role

As a Staff Machine Learning Engineer, you will transform research into production-grade ML systems for an AI system that understands context, plans actions, and carries work forward. This role focuses on the execution layer, including training pipelines, inference systems, evaluation tooling, and deployment.

Responsibilities

• Build and own end-to-end ML pipelines spanning data, training, evaluation, inference, and deployment
• Fine-tune and adapt models using state-of-the-art methods such as LoRA, QLoRA, SFT, DPO, and distillation
• Architect and operate scalable inference systems, balancing latency, cost, and reliability
• Design and maintain data systems for high-quality synthetic and real-world training data
• Implement evaluation pipelines covering performance, robustness, safety, and bias, in partnership with research leadership
• Own production deployment, including GPU optimization, memory efficiency, latency reduction, and scaling policies
• Collaborate closely with application engineering to integrate ML systems cleanly into backend, mobile, and desktop products
• Make pragmatic trade-offs and ship improvements quickly, learning from real usage
• Work under real production constraints: latency, cost, reliability, and safety

Requirements

• Experience building or shipping real ML systems
• Comfortable working with large models and understanding their failure modes
• Production-grade code writing skills and care about system correctness
• Self-directed, pragmatic, and take full ownership of outcomes
• Clear communication and collaboration skills in small, high-trust teams

Skills

* Required skills