JAX Jobs

NVIDIA is seeking a Senior Deep Learning Software Engineer to join their Algorithmic Model Optimization Team. This role focuses on optimizing generative AI models, including LLMs and diffusion models, for maximum inference efficiency. The team utilizes techniques like neural architecture search, pruning, sparsity, and quantization, and develops an innovative software platform for automated deployment. The engineer will contribute to applied research and the development of this software, which is used both internally at NVIDIA and externally by other AI development teams. This is an opportunity to push the boundaries of inference efficiency and large-scale automated deployment, working with high-level frameworks and improving high-performance kernel implementations.

$184k - $357k

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

Anthropic

Reinforcement learning (RL) is crucial for Claude's ability to reason, write code, and act autonomously over long horizons. This role is part of the team responsible for building and maintaining the RL training system, which is used to train production models and for researchers across Anthropic to run their experiments. The team collaborates closely with research teams company-wide on the science and engineering required to scale RL effectively. As a Research Engineer, you will be at the heart of RL at Anthropic, with a direct view of RL training at the frontier, as the system you own supports both production and research runs. You will work with collaborators across research teams to understand system performance, identify areas of fragility, and drive future improvements.

$500k - $850k

SambaNova is seeking a talented and driven ML performance engineer to optimize and scale state-of-the-art foundation models on SambaNova's reconfigurable dataflow platform. You will work hands-on with advanced models to push the limits of throughput, latency, and efficiency. This role bridges the gap between deep learning and systems performance, collaborating across compiler, runtime, and hardware layers to deliver world-record performance for large-scale AI inference.

$180k - $255k

Anthropic

Anthropic is dedicated to building AI systems that are safe, reliable, and steerable, aiming to benefit both users and society. This role is central to advancing Reinforcement Learning (RL), the core technology enabling Claude's reasoning, coding, and autonomous capabilities. The RL Scaling team focuses on how RL performance, stability, and learning efficiency evolve with increasing model size, episode length, and compute power. You will be instrumental in developing and scaling next-generation RL algorithms and architectures, from initial research to large-scale deployment, while deeply understanding and addressing the challenges that arise at scale. This position bridges research and engineering, requiring you to build the systems that accelerate iteration and experimentation, and to tackle complex, unsolved problems in Anthropic's largest RL runs.

$500k - $850k

Joining NVIDIA's DGX Cloud AI Efficiency Team means contributing to the infrastructure that powers our innovative AI research. This team focuses on developing tools for optimizing efficiency and resiliency of AI workloads, including pre-training, post-training, and inference. Our objective is to deliver a stable, scalable environment for AI researchers, providing them with the necessary resources and scale to foster innovation. As a senior DGX Cloud AI Infrastructure software engineer, you will have the opportunity to work on innovative technologies that power the future of AI and data science and be part of a dynamic, diverse, and supportive team that values learning and growth.

$184k - $357k

Joining NVIDIA's DGX Cloud AI Efficiency Team means advancing the performance, efficiency, and resiliency of large-scale AI workloads. You will help AI researchers and platform teams understand end-to-end behavior across GPUs, networking, storage, and software stacks. Your work will shape scalable DGX Cloud systems, turn complex measurements into prioritized engineering decisions, and continuously raise the performance and reliability of AI workloads. Join a technically diverse team of infrastructure experts to unlock more efficient AI at scale.

$224k - $431k

PostEra is seeking a Machine Learning Researcher to spearhead the development of an agentic research vertical. This role involves leveraging agentic systems to automate the creation of mechanistic models for biochemical and physiological processes, and to analyze biological data for target validation. You will collaborate closely with chemists and biologists to guide drug discovery decisions using these models. A key focus will be on developing machine learning methods capable of rapid adaptation to new drug discovery challenges with limited labeled data, particularly in molecular and tabular in-context learning and building foundation models from proprietary multimodal data. You will be responsible for the entire research loop, from defining tasks and constructing datasets to training and scaling models, performing rigorous ablations, and translating successful methods into practical capabilities for PostEra's scientists. While prior drug discovery experience is not mandatory, a strong motivation to learn the domain and collaborate with interdisciplinary scientists is essential.

The Core ML team is seeking an engineer to map novel algorithms for efficient large-scale AI training and inference to the Cerebras architecture. This role involves determining when these algorithms outperform competing approaches and how their advantages scale with models, workloads, and hardware. You will combine analytical performance modeling, empirical benchmarking, and hands-on prototyping to characterize the efficiency frontiers of emerging ML algorithms. Your work will span kernel-level and end-to-end performance, influencing research directions, implementation on current systems, and future hardware/software capabilities.

The Core ML team is seeking an engineer to bridge the gap between novel machine learning research and efficient execution on Cerebras systems. You will work across ML frameworks, compilers, runtimes, and low-level kernels to implement new algorithmic capabilities, diagnose performance bottlenecks, and transform research prototypes into robust, high-performance demonstrations. Depending on your background, your work may emphasize runtime capabilities such as token orchestration, scheduling, communication, and distributed execution; low-level kernel development for novel ML operations; or a combination of both. This role is crucial for advancing the capabilities of Cerebras' unique AI chip architecture.

Chai Discovery is building the computer-aided design suite for molecules, with major pharmaceutical companies already using their platform to accelerate drug discovery. They are at the forefront of reinventing life sciences through AI, developing frontier models that understand biochemical structure and interaction. This role is an opportunity to push the boundaries of AI drug design alongside a skilled and dedicated team.

Together AI

The Inference Research team is dedicated to building the next generation of efficient, scalable, and reliable serving systems for large foundation models, advancing open and transparent AI. This role operates at the intersection of model architectures, high-performance systems engineering, and hardware optimization, focusing on co-designing software, algorithms, and models to reduce the cost and latency of AI systems. As a research intern, you will explore distributed inference, compiler-aware optimization, and novel inference-time computation strategies, co-designing and implementing cross-layer optimizations across models, systems, and hardware, with a focus on KV cache design and large-scale serving architectures. Projects aim to unlock unprecedented performance and scale for foundation models, enabling faster serving, larger model deployment, and robust evaluation under realistic serving workloads.

Together AI

The Inference Research team is dedicated to building the next generation of efficient, scalable, and reliable serving systems for large foundation models, advancing open and transparent AI. This role operates at the intersection of model architectures, high-performance systems engineering, and hardware optimization, focusing on co-designing software, algorithms, and models to reduce the cost and latency of AI systems. As a research intern, you will explore distributed inference, compiler-aware optimization, and novel inference-time computation strategies, co-designing and implementing cross-layer optimizations across models, systems, and hardware.

Together AI

The Agents team focuses on building, aligning, and scaling advanced AI systems capable of handling complex, multi-step tasks and workflows across text and speech, particularly in agentic and scientific domains. This role sits at the intersection of agent capabilities, human-computer interaction, and infrastructure, exploring areas like post-training methods for agentic behavior and evaluation frameworks for open-ended tasks. As a research intern, you will contribute to cutting-edge agentic AI challenges, addressing issues of alignment, reliability, and scalability. Projects may involve developing new training techniques for self-learning and long-horizon reasoning, curating datasets for scientific and agentic tasks, analyzing agentic behavior failure modes, or building scalable agent operation infrastructure.

Together AI

The Agents team investigates how to build, align, and scale frontier AI systems capable of complex, multi-step tasks across text and speech, focusing on agentic and scientific domains. This role sits at the intersection of agent capabilities, human-computer interaction, and infrastructure, exploring areas like post-training methods for agentic behavior and evaluation frameworks for open-ended tasks. As a research intern, you will tackle challenges in alignment, reliability, and scalability, potentially working on new training recipes for self-learning, curating datasets for non-deterministic tasks, studying agentic behavior failure modes, or building large-scale agent operation infrastructure.

WRITER is a company focused on orchestrating AI-powered work for leading enterprises, aiming to expand human capacity through superintelligence. Their platform enables companies to build and deploy AI agents grounded in their data and powered by enterprise-grade LLMs. WRITER is a rapidly growing company in the enterprise generative AI space, seeking talented individuals to join their mission to create a better future of work with AI.

$199k - $325k

As an AI engineer at WRITER, you will be instrumental in shaping how enterprises leverage superintelligence. This role involves building tangible AI solutions that power the future of work for leading global companies. Your contributions will directly influence the performance, scalability, and ethical alignment of our advanced LLMs and AI agents, enabling businesses to achieve unprecedented productivity and innovation through AI grounded in their data.

$198k - $259k

Thinking Machines is building AI that extends human will and judgment, focusing on training frontier models, developing tools for model customization, and crafting interfaces for human-AI communication. This role is crucial for shaping the fundamental reasoning capabilities of our models by owning the late-stage training process. It involves a blend of fundamental research and practical engineering, making it ideal for individuals comfortable working at the intersection of pre-training and post-training.

$350k - $475k

We are seeking a mission-driven Developer Relations Manager focused on Foundational AI Research to engage leading academic labs advancing the next generation of AI models, systems, and methods. In this role, you will work directly with top researchers building frontier AI systems, including large language models, multimodal models, reasoning systems, training methods, inference systems, model serving, and scalable AI infrastructure. You will help researchers adopt NVIDIA’s AI and accelerated computing platforms to push the boundaries of model performance, efficiency, and scale.

$152k - $288k