Director of Engineering, Data Labs

What you'll do

• Own the multi-year technical roadmap and architectural direction for shared platforms and engagement-specific solutions.
• Define evaluation and data strategies, including benchmarking, reusable data assets, privacy, licensing, and contamination risk.
• Lead engineering managers and senior technical staff; advise clients and executives and coordinate with research, product, and commercial teams.

What they ask for

• 10+ years in software engineering, with significant experience building ML or AI systems.
• 5+ years in engineering leadership, including managing managers across multiple teams.
• Track record setting multi-year technical strategy and making commercially successful platform investments.
• Deep, current understanding of AI training and evaluation, plus hands-on familiarity with LLM training pipelines and experience building benchmarking, data curation, or RL infrastructure.

Nice to have

• Experience at an AI services firm, applied research consultancy, frontier lab, or enterprise AI product company.
• Familiarity with data licensing, synthetic data generation, or contamination detection involving client data.

Pay

$252,000 — $300,000 USD base salary

Tools

LLM training pipelines, RLHF/RLAIF, RL environments, synthetic data

AI focus

Leads strategy for AI training and evaluation infrastructure, including benchmarking, data pipelines, RL environments, and evaluation methods.