FSDP Jobs

Databricks

Databricks is seeking a Senior Staff Software Engineer to work on the AI Runtime system, which powers the world's largest AI platform. This serverless product enables companies to train their own models using enterprise data, similar to how frontier labs operate. The role involves tackling complex technical challenges to advance AI Runtime's architecture, reliability, and developer experience for both humans and AI agents. You will contribute to shaping the long-term technical direction of AI training infrastructure, anticipating industry trends, and optimizing training efficiency and cost across various model architectures and GPU accelerators.

$229k - $343k

Databricks

Databricks is seeking a Senior Software Engineer for its AI Runtime (AIR) team. AIR is a managed platform designed for large-scale GPU training and fine-tuning of AI models, providing customers with on-demand access to accelerators and a serverless experience that simplifies the complexities of provisioning, scheduling, and orchestrating multi-node jobs. As a Senior Software Engineer on AIR, you will be instrumental in building and scaling the systems that ensure large-scale training is fast, reliable, and effortless. You will lead the architecture and evolution of the managed GPU training stack, focusing on areas such as scheduling, distributed training performance, fault tolerance, and the developer experience for large-scale job operations. Beyond hands-on system development, you will contribute to the technical vision for AIR, mentor engineers, and collaborate with product, research, and platform teams to expand the impact of custom AI training at Databricks.

$160k - $225k

Databricks

Databricks is seeking a Staff Software Engineer for its AI Runtime (AIR) team. AIR is a managed platform designed for large-scale GPU training and fine-tuning of state-of-the-art AI models, providing customers with on-demand access to accelerators and a serverless experience. As part of this role, you will be instrumental in building and scaling the systems that ensure fast, reliable, and effortless large-scale training. You will influence the architecture and development of the managed GPU training stack, focusing on areas like scheduling, distributed training performance, fault tolerance, and the overall developer experience for operating jobs at scale. This position also involves defining the long-term technical vision for AIR, mentoring senior engineers, and collaborating with product, research, and platform teams to expand the impact of custom training at Databricks.

$190k - $265k

Prime Intellect is building the open superintelligence stack, providing infrastructure for AI labs. Their platform, Lab, unifies compute, environments, evaluations, and training/deployment for post-training at scale, including SFT, RL, and agent workflows. They are developing open-source models for long-horizon tasks and the platform their research team uses. The company has raised significant funding and is looking for individuals passionate about frontier research, infrastructure, and go-to-market strategies in a nascent category.

$150k - $350k

Together AI

The Speculative Decoding team at Together AI focuses on developing draft models and algorithms to accelerate large language model generation without altering outputs. Their work integrates model training, inference algorithms, and serving systems, optimizing all three for reduced cost and latency. As a research intern, you will explore open questions in speculative decoding, including new drafter architectures, verification schemes, knowledge distillation, and adaptive drafters. You will train and fine-tune draft models at scale on GPU clusters and evaluate your solutions against realistic serving workloads, such as long-context and agentic traffic.

Together AI

The Speculative Decoding team at Together AI focuses on developing draft models and algorithms to accelerate large language model generation without altering outputs. Our work spans model training, inference algorithms, and serving systems, aiming to reduce generation cost and latency. As a research intern, you will explore open questions in speculative decoding, including new drafter architectures, verification schemes, knowledge distillation, and adaptive drafters. You will train and fine-tune draft models at scale on GPU clusters and evaluate your ideas against realistic serving workloads, such as long-context and agentic traffic. Projects are designed to address key research questions in speculative decoding, leading to faster generation on frontier models, drafters that adapt to changing workloads, and robust evaluation under real traffic.

Cohere

Cohere is seeking a Member of Technical Staff to focus on post-training large language models (LLMs) using reinforcement learning and developing methods for improved generalization. This role involves designing training recipes, environments, and evaluations to ensure models learn skills effectively and generalize beyond their training data. You will collaborate with data infrastructure, evaluation, and pre-training teams to translate research findings into robust training procedures for production models. The ideal candidate is passionate about advancing AI capabilities and contributing to the widespread adoption of AI in enterprise solutions.

CA$295k - CA$535k

Luma is seeking a Research Scientist/Engineer to build the systems that enable reinforcement learning (RL) at a frontier scale. This role involves coupling policy optimization with large fleets of inference workers, agentic environments, and reward/verification systems to translate model behavior into learning signals. RL is crucial for Luma's models to evolve from capable to useful. This is a full-loop systems problem encompassing training, rollout generation, environment execution, and reward computation across thousands of GPUs, requiring speed, stability, and correctness. The ideal candidate has experience with post-training LLMs using RL, building environments and verifiers, and debugging large-scale asynchronous rollout pipelines.

Luma is seeking a Research Scientist / Engineer to build and optimize the distributed systems that train large-scale multimodal models across thousands of GPUs. This role focuses on advanced parallelism, training stability, and utilization across massive clusters, requiring deep expertise in distributed PyTorch and CUDA. The goal is to provide researchers with reliable, efficient, and scalable infrastructure for innovation.

$195k - $395k

Luma is seeking a Research Scientist / Engineer to build and optimize the distributed systems that train large-scale multimodal models across thousands of GPUs. This role focuses on advanced parallelism, training stability, and utilization across massive clusters, requiring deep expertise in distributed PyTorch and CUDA. The goal is to provide researchers with reliable, efficient, and scalable infrastructure for innovation.

We are a dedicated research lab focused on building, understanding, using, and risk-managing foundation models. Our mission is to advance AI research, cultivate the next generation of AI builders, and make significant contributions to a knowledge-driven economy. As part of our team, you will work on the core of cutting-edge foundation model training alongside world-class researchers, data scientists, and engineers. You will tackle fundamental and impactful challenges in AI development, contributing to groundbreaking AI solutions that have the potential to reshape industries. Strategic and innovative problem-solving skills are essential for establishing our institution as a global hub for high-performance computing in deep learning.

$150k - $450k

We are a dedicated research lab focused on building, understanding, using, and risk-managing foundation models. Our mission is to advance research, nurture the next generation of AI builders, and drive transformative contributions to a knowledge-driven economy. As part of our team, you will have the opportunity to work on the core of cutting-edge foundation model training alongside world-class researchers, data scientists, and engineers. You will tackle fundamental and impactful challenges in AI development, participating in the creation of groundbreaking AI solutions that have the potential to reshape entire industries. Strategic and innovative problem-solving skills are essential for establishing our institution as a global hub for high-performance computing in deep learning.

$150k - $450k

Mirage is seeking an ML Engineer to build and scale the systems powering their video generation models. This role sits at the intersection of research and systems engineering, focusing on making advanced models faster, more efficient, and capable of ultra-low latency, real-time generation. You will work on novel modeling approaches, training objectives, scaling strategies, and inference optimization and efficiency to bring cutting-edge models into production.

$175k - $300k

Nunchux AI is building infrastructure to make multimodal generative AI faster, cheaper, and easier to build upon. We are seeking a Machine Learning Engineer focused on post-training and evaluation to enhance the efficiency and quality of visual generative models. In this role, you will develop and validate post-training techniques, curate and manage data pipelines for training and evaluation, and build robust evaluation systems to measure model performance. You will also benchmark models against industry standards, ensure quality, and integrate cutting-edge research into production workflows.

$180k - $250k