Distributed Training Jobs

Nebius is building a full-stack AI cloud platform to support developers and enterprises in AI/ML infrastructure, from data and model training to production deployment. This role focuses on the infrastructure for large-scale AI training and model post-training capabilities, specifically for frontier model improvement. The work involves distributed systems, GPU performance, model training frameworks, RL pipelines, and production engineering. The Senior Machine Learning Engineer will own ML work end-to-end, translating ambiguous goals into concrete experiments, implementing and debugging training and RL recipes, building supporting systems, and delivering measurable improvements in model quality, throughput, and reliability. This is a hands-on role requiring independent debugging of both model behavior and distributed training failures.

$195k - $262k

We are building AI that changes how people capture, understand, and act on conversations and meetings. As Director of AI Research, you will lead research and development across automatic speech recognition (ASR), speaker identification (SID), large language models (LLMs), and audio language models. Your work will shape our AI capabilities, product direction, and long-term research strategy. This is a hands-on leadership role for someone who combines research depth with experience building and deploying AI systems at scale. You will set technical priorities, guide model and infrastructure decisions, and work directly with the team on challenging research and engineering problems. Partnering closely with Product, Engineering, and Data teams, you will turn research advances into reliable product capabilities. You will also build the team, experimentation practices, and technical foundation needed to move quickly while maintaining high standards for quality and performance.

$244k - $313k

Sieve is seeking its first Robotics Researcher to lead the training and evaluation of world-action models (WAMs) and 3D perception systems. This role focuses on understanding how data shapes robot capabilities, connecting data curation and labeling to measurable gains in robot learning. You will manage projects from inception to completion, identifying model shortcomings, determining data needs, setting up experiments, and testing results on unseen tasks and environments. A significant portion of this work involves 3D, transforming raw multimodal and egocentric video into actionable data for robot learning by incorporating geometry, pose, and action. Simulation will be used as a tool for evaluation and augmentation when beneficial, but not as the primary focus.

Reflection ai

Reflection is a research lab dedicated to making intelligence open and accessible for everyone. We build open models that empower individuals to control their intelligence and shape the future of AI. This role focuses on the foundational aspects of AI development, specifically in pre-training data, contributing to the creation of open foundational models. You will be part of a talented team, helping to define the company's future and the future of open AI.

Scale AI

Scale's ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform powers MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs, as well as data quality evaluation. You will work closely across Scale’s ML teams and researchers to build the foundation platform that supports all our ML research and development, enabling the next generation of LLM training, inference, and data curation.

$190k - $237k

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

Plaid is seeking a Staff Machine Learning Engineer to join the Data Foundation & AI team. This team builds the shared ML and AI infrastructure that powers intelligent capabilities across Plaid's product suite, transforming unique financial network data into scalable, general-purpose representations. The role involves working at the intersection of machine learning infrastructure, applied AI, and distributed systems to establish the core AI platform that enables innovation. The Staff ML Engineer will lead the technical strategy and development of Plaid’s foundation models, driving key decisions across pretraining objectives, model architecture, and fine-tuning approaches. This position requires establishing rigorous evaluation frameworks, building scalable pipelines, and partnering with teams across the organization to define product integrations with foundation models. As a senior technical leader, you will mentor engineers, elevate engineering standards, and represent Plaid's AI and machine learning capabilities externally.

$249k - $368k

Etched is building AI systems that accelerate its own development. As a Research Engineer on the RL Frontiers team, you will train proprietary frontier models to automate kernel development, ASIC engineering, production pipelines, and 3-D hardware operating systems. You will use proprietary simulators and environments to create custom data mixes and post-train models to SOTA performance on the company's hardest engineering tasks. The company is focused on inference and bets on transformer architectures, aiming to capture the entire inference market. Etched is a fully in-person team in San Jose, valuing engineering skills and expecting technical staff to contribute to both engineering and research across disciplines.

From $400k

Thinking Machines is building AI that extends human will and judgment. We are developing Tinker, a fine-tuning API that empowers researchers and developers to customize frontier AI models. This role focuses on building and enhancing our training systems for Tinker, specifically involving RL systems, numerics, and kernels, to enable users to train models with their own data and algorithms.

$350k - $475k

ElevenLabs is seeking an engineer to join their research infrastructure team to ensure their NVIDIA GPU clusters are fast, reliable, and performant. This is a builder-operator role with significant autonomy, where your impact will be directly measured by training throughput and researcher velocity. You will be responsible for the entire stack beneath the training code, from OS images and NVIDIA drivers to high-speed networking and job scheduling. The role involves both hands-on hardware work and writing automation to eliminate manual tasks, with a focus on maintaining cluster security and performance.

Genmo is a research lab developing sophisticated video world models to understand, simulate, and interact with the physical world, aiming to unlock the right brain of AGI. We are seeking an exceptional Research Scientist to focus on alignment and post-training techniques for large-scale video generation models. This role is at the forefront of ensuring our diffusion-based video models reliably produce high-quality, physically accurate, and safe outputs that align with human preferences and values.

Deepgram is a leading platform for the Voice AI economy, offering real-time APIs for speech-to-text, text-to-speech, and building voice agents at scale. We empower over 1,300 organizations and 200,000 developers to create voice offerings powered by our advanced foundation models, accessible via cloud APIs or self-hosted solutions. Our AI-first approach means every team member is expected to actively use, experiment with, and build AI tools into their daily work, driving innovation and performance. We operate at the rapid pace of AI, requiring adaptability, continuous learning, and a proactive mindset to solve customer challenges and push technological boundaries.

$216k - $338k

Deepgram is a leading platform for Voice AI, providing real-time APIs for speech-to-text and text-to-speech, enabling developers to build production-grade voice agents at scale. We are seeking researchers who are passionate about solving customer challenges by improving our AI models. This role involves identifying model limitations, designing evaluations, curating data, fine-tuning models, and shipping solutions to production within weeks. The ideal candidate will have an AI-first mindset, be comfortable experimenting with new AI tools and models, and thrive in a fast-paced, evolving environment.

$216k - $338k

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

We are seeking a Senior Forward Deployed Engineer to lead technical engagements with partners and customers, focusing on NVIDIA's open model portfolio. The primary mission is to transform open models into production-ready AI solutions tailored to specific domains, covering the entire lifecycle from post-training to harness optimization. This role involves collaborating closely with NVIDIA's partner ecosystem, co-leading customer engagements, and developing resources that enable partners to scale their AI initiatives. You will work hands-on to build custom AI solutions, from initial customer conversations through to production deployment, ensuring models are optimized for performance and cost-effectiveness.

$184k - $357k

NVIDIA is seeking a founding Director to establish and lead its Forward Deployed Engineering (FDE) organization for open models, specifically focusing on NVIDIA Nemotron and NVIDIA Cosmos across North America. The core mission is to transform open-source models into production-ready AI solutions tailored to specific domains, leveraging NVIDIA's partner ecosystem. This role involves setting the strategic direction for North America, building and scaling the FDE team, and fostering strong relationships with partners, customers, and NVIDIA leadership. The FDE team will work collaboratively with top partner engineering and research teams, co-leading joint customer engagements and developing best practices to ensure partner success and scalability. The ultimate goal is to empower organizations to build, own, and operate their AI on open-source models.

$320k - $489k

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.

Prime Intellect is building the open superintelligence stack, providing infrastructure for AI labs. Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment for post-training at frontier scale. We are developing open-source models trained end-to-end for long-horizon tasks like autonomous research, alongside the full-stack platform our research team utilizes. We are seeking individuals passionate about building at the intersection of frontier research, real infrastructure, and go-to-market for a nascent category.

$150k - $350k