Member of Technical Staff, Research (EU)

The role

You will architect and execute a research agenda to advance model reasoning at scale. You will design tasks, diagnose failure modes, and partner with AI research teams on datasets and benchmarks.

What you will do

• Architect and execute a research agenda to advance model reasoning at scale
• Build long-horizon agentic tasks and graders
• Diagnose failure modes by reading trajectories
• Partner with AI research teams on datasets and benchmarks
• Identify, scope, and run long projects for scaling data toward AGI
• Work with engineering on data pipelines, internal tooling, and deep learning implementations

Required qualifications

• Strong software engineering and deep Python
• Experience building evaluations, RL environments, agent harnesses, verifiers, or execution sandboxes
• Experience shipping research into production, particularly post-training, distillation, and high-stakes evaluation
• Experience working on large-scale agent systems including orchestration frameworks, tool APIs, distributed execution, observability, and logging
• Ability to get to ground truth in unfamiliar domains by building something and reading outputs
• Ability to notice misspecified tasks, ambiguous prompts, and graders that can be gamed
• Thoughtful perspective on the societal and safety impacts of deploying general-purpose AI systems

Nice to have

• A PhD (CS, ML, NLP) and publications at NeurIPS, ICML, or ICLR
• Work on public benchmarks or task suites, for example Terminal-Bench, SWE-bench-style harnesses, or HCAST
• RLHF or RLAIF experience and a view on how training choices show up in model behavior
• Experience running work through large expert or annotation operations

Benefits

• Health
• dental
• vision
• flexible PTO

About the company

Abundant is an applied research lab focused on scaling reinforcement learning for safe and reliable agentic capabilities. The team includes researchers, roboticists, founders, and operators whose work includes the Waymo Driver.