distributed ML systems Jobs

Prime Intellect is building the open superintelligence stack, a full-stack system for post-training at frontier scale, from SFT and RL to tool use and agent workflows. We are developing open-source models trained end-to-end for long-horizon tasks like autonomous research, and the platform our own research team uses to build them. We are seeking individuals passionate about building at the intersection of frontier research, real infrastructure, and go-to-market for a nascent category. This role will focus on developing the algorithms and systems used to train our open models with reinforcement learning, with opportunities to specialize in RL algorithms, scaling research, or training frameworks.

$150k - $350k

Databricks

Databricks AI is seeking a Principal AI Research Scientist to lead a team focused on advancing the state of the art in large-scale machine learning, particularly in LLM training and inference efficiency. This role involves defining and executing a research roadmap to improve how customers train, serve, and adapt LLMs at scale, working closely with product, data, and engineering leaders. The ideal candidate will drive algorithmic innovations, optimize ML systems for distributed training and inference, and translate research breakthroughs into customer-impacting capabilities within the Databricks AI platform. This position also requires fostering a culture of scientific excellence, representing Databricks AI externally, and mentoring research talent.

$270k - $340k

Databricks

Databricks AI Research is seeking a Principal Research Scientist – Scaling to lead a team focused on advancing the state of the art in large-scale machine learning, particularly in LLM training and inference efficiency. This role involves defining and executing a research roadmap to improve how customers train, serve, and adapt LLMs at scale, working closely with product, data, and engineering leaders. The goal is to push the boundaries of LLM efficiency beyond existing models, exploring novel algorithms, systems, and infrastructure improvements. You will drive independent research agendas and collaborate on low-level implementation details to bring cutting-edge methods into production and enhance the Databricks AI platform.

$280k - $350k

We are seeking a Research Scientist to focus on Agentic Data & Benchmarking. This role involves designing and executing evaluations for agentic capabilities, including multi-step reasoning, tool use, and long-horizon planning. You will build and maintain robust evaluation harnesses to ensure reliable, large-scale benchmarking against model checkpoints, identifying regressions and monitoring model health. Additionally, you will conduct experiments to understand how various factors like prompting, sampling, and environment design influence agentic performance on both internal and public benchmarks. A key part of this role is diagnosing anomalous evaluation results during training, pinpointing the root cause (model, data, harness, or infrastructure), and communicating findings clearly. You will also be responsible for sourcing, generating, and curating high-quality agentic training data, including trajectories and tool-use traces, and designing and scaling RL environments and reward signals. Managing technical relationships with external data vendors and domain experts, evaluating data quality, and developing QA frameworks to ensure data and benchmark integrity are also crucial aspects of this position. You will contribute to technical reports, research publications, and open-source benchmarks and tooling, partnering with research and product teams to translate capability goals into measurable data and evaluation artifacts.

$150k - $450k