ML Engineer

About the role

This is a rare opportunity to join a very early stage AI startup and take full ownership of building a critical machine learning system from the ground up. You will design and deliver the core training and remediation loop that ensures AI systems behave safely and reliably in production, giving you genuine 0 to 1 engineering scope with immediate impact. The company is an early stage AI business focused on improving the safety and reliability of AI systems in production environments. Their platform continuously tests AI applications, detects unsafe or unintended behaviour, and deploys targeted fixes. Operating at the intersection of machine learning, security, and infrastructure, they are tackling a rapidly growing challenge as organisations scale their use of AI. With a small, highly technical team, they offer close collaboration with leadership and significant ownership from day one.

Responsibilities

• Build and own end to end training and remediation pipelines for AI systems, from signal detection through to deployment and monitoring
• Develop reinforcement learning and preference optimisation workflows, including approaches such as DPO and RLHF
• Translate behavioural issues into structured training data and deploy effective model improvements
• Create scalable evaluation and testing systems to ensure fixes perform reliably in production
• Work across multiple models and deployments, turning one off fixes into reusable tooling
• Improve system performance, reliability, and efficiency as the product evolves

Skills

• Strong commercial experience in machine learning engineering, with deep expertise in Python and PyTorch
• Proven ability to train, fine tune, and deploy models in production environments
• Hands on experience with reinforcement learning or preference optimisation techniques such as DPO, RLHF, or PPO
• Strong understanding of end to end ML pipelines, from data preparation through to monitoring
• High standards for code quality, architecture, and readability
• Comfortable operating in an early stage environment with ambiguity and ownership
• Experience designing evaluation systems or working on AI safety, trust, or security is beneficial

Pay

Base salary between $200,000 and $240,000, with flexibility for the right candidate, plus a meaningful early‑stage equity package.

Benefits

• Comprehensive benefits including healthcare, retirement, and generous holiday allowance
• The opportunity to build a core platform from scratch and shape technical direction
• Close collaboration with founders and engineering leadership