Frontier AI Applied Researcher — Remote & Sponsorship

OpenKrill; United States; Remote; USD 150,000 - 300,000; Full time

Benefits offered by this job

Cash compensation + equity

Remote work

Visa sponsorship and relocation

Professional development budget

Team off-sites & conferences

Job summary

Prime Intellect is shaping the frontier of AI infrastructure, unifying post-training workflows and evaluation into a production-grade platform. You will advance continual learning, RL, and memory-driven methods, and work closely with customers to turn research into deployable capabilities.

The role emphasizes external collaboration, reproducible experiments, and building open research, with opportunities across frontier AI and tool-use at scale.

Qualifications

• Continual or online learning, RL, meta-learning, memory systems, post-training data loops.
• Hands-on experience building and debugging model-training, post-training, agent, evaluation loops.
• Strong experimental judgment with clear failure attribution and adaptability.
• Strong Python and ability to build runnable artifacts for others.
• Comfort owning ambiguous problems and keeping partners updated.

Responsibilities

• Applied Research at Prime: turn workflows into tasks, environments, evaluations, and reward signals.
• Run post-training experiments against baselines and deploy what works.
• Collaborate with customers, users, or research partners while pursuing a research agenda.
• Build reusable research, open-source systems, and product capabilities.

Skills

Continual learning

Online learning

Reinforcement Learning

Meta-learning

Memory systems

Post-training data loops

Adaptive production ML

Evaluation under changingDistributions

Python

Job description

Prime Intellect is shaping the frontier of AI infrastructure, unifying post-training workflows and evaluation into a production-grade platform. You will advance continual learning, RL, and memory-driven methods, and work closely with customers to turn research into deployable capabilities.

The role emphasizes external collaboration, reproducible experiments, and building open research, with opportunities across frontier AI and tool-use at scale.