AI Technical Lead

Role Overview

This is a remote contract opportunity for an AI Technical Lead based in Singapore, with work available from anywhere. The position is focused on advancing frontier AI models through careful evaluation, failure investigation, and repeated refinement. A major part of the job is to build machine-learning-oriented data systems, turn real-world challenges into structured evaluation methods, and partner with researchers and subject-matter specialists to improve model performance in areas like finance, healthcare, and engineering. The role has a direct influence on how AI systems learn, reason, and operate in high-stakes settings by linking human expertise with advanced AI training workflows.

Payout

The stated compensation is $600k to $2M per year.

Key Responsibilities

• Lead research and evaluation work from start to finish, including defining the problem, shaping the data approach, setting quality standards, and checking whether the signals are valid.
• Build data systems for machine learning that include task definitions, annotation guidelines, scoring rubrics, incentive structures, and pipelines tuned for better downstream model outcomes.
• Review model and system breakdowns to uncover root causes, unusual cases, and practical improvement areas.
• Convert unclear real-world behavior into structured evaluation designs and new data categories.
• Continuously refine evaluations, datasets, and feedback loops to raise model and system performance.

Required Background

The role calls for strong judgment in research signals for AI/ML systems, including the ability to design evaluations and validate experimental outcomes. Candidates should have a solid foundation in ML-oriented data design, especially creating annotation schemas and rubrics that align with training goals. The position also requires the ability to connect operations insights with research work, bridging domain knowledge and technical delivery. Practical experience with reinforcement learning environments or similar ML evaluation setups is important, along with experience building and improving data pipelines that preserve quality while moving quickly in production settings.

Additional Information

This opportunity is part of work that supports advanced AI systems used by labs and enterprises to train foundation models and develop dependable AI agents. The environment includes an AI recruiter agent, a high-performance data platform, and performance monitoring tools, allowing the work to scale across global expert networks.

Equal Opportunity

Hiring decisions are based on skills and expertise. All qualified applicants are considered regardless of background, experience, or prior work history, and review is based only on technical ability and qualifications.