PyTorch Jobs

HUD is seeking a Product Engineer to transform significant product challenges into tangible user experiences across its AI data platform and marketplace. This role involves collaborating with product, design, engineering, research, and go-to-market teams to identify user pain points in AI data creation and training, define product improvements, and develop solutions. The position blends product strategy, interaction design, and full-stack development, requiring the ability to translate complex technical workflows into clear and user-friendly interfaces while retaining necessary detail.

$100k - $225k

Tennr is seeking a high-agency Senior Backend Engineer to connect advanced ML research with practical product delivery. You will architect and develop agentic workflows designed to tackle complex healthcare processes, addressing infrastructure, workflow, and user experience challenges within the U.S. healthcare system. This role involves constructing data pipelines, evaluation frameworks, and scalable, production-ready agentic systems. You will be tasked with identifying and implementing the most suitable tools and models for each specific workflow, ensuring optimal technology utilization.

$190k - $215k

As a Senior Applied AI/ML Scientist on the Search team, you will shape the technical vision, machine-learning algorithm strategy, and system design behind Faire's Search functionality. You will advance real-time search and recommendation systems that power next-generation shopping experiences by working at the frontier of algorithms, combining query understanding, deep learning, transformer-based sequential modeling, graph neural networks, and structured behavioral data to return hyper-relevant, personalized products and brands for every user query. This is a chance to influence the end-to-end personalized discovery experience at Faire within a high-scale, deeply multi-modal environment, collaborating closely with a talented team of scientists and engineers.

$211k - $291k

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

Datadog AI Research (DAIR) is seeking a Research Scientist to partner with Research Engineers on fundamental research problems. The role involves translating research advances into products by collaborating with Datadog's product and engineering teams. The team focuses on high-risk, high-reward problems in cloud observability and security, building on existing AI-powered solutions. The research areas include developing multimodal foundation models for understanding distributed systems and training autonomous agents for observability tasks like incident response and code repair.

$320k - $400k

Latent is seeking a Machine Learning Engineer, Research, to lead the design and development of innovative modeling approaches that push the boundaries of clinical intelligence. This role involves driving research from initial problem definition to validated outcomes, influencing how models learn from longitudinal patient data. We are looking for senior and staff-level engineers adept at managing critical research challenges from inception to completion, with a focus on problems that directly impact patient well-being.

$225k - $300k

Latent is seeking a Machine Learning Engineer to join their team and build systems that run in real clinical workflows. This role involves owning the design, development, and operation of production-grade ML systems from ambiguous problem definition through to reliable production deployment. The ideal candidate will drive systems end-to-end, setting technical direction and taking ownership of critical systems that directly impact real patient outcomes. This is an opportunity to work on mission-critical problems at the intersection of AI and healthcare within a fast-growing, early-stage company backed by top-tier investors.

$225k - $300k

NVIDIA is seeking a Senior Software Engineer to lead the bring-up, triage, benchmarking, analysis, and optimization of distributed training and inference workloads across NVIDIA GPU platforms at the largest scales. In this role, you will set technical direction for communication libraries, model frameworks, and inference/training stacks to ensure state-of-the-art LLM workloads run efficiently and reliably at scale. You will lead deep performance and reliability investigations on multi-GPU and multi-node deployments, define how new platforms are benchmarked and qualified, and build the resilience and failure-attribution capabilities essential for large clusters. This is a hands-on, senior individual-contributor role for an engineer experienced at the intersection of deep learning systems, GPU performance, distributed computing, and large-scale operations.

$184k - $357k

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.

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

Tavus is building the human layer of AI, aiming to make human-AI interaction as natural as face-to-face communication. We pioneer research in multimodal AI for modeling human communication (language, audio, video) and generating audio-visual avatar behavior, powering applications from text-to-video avatars to real-time conversational video. We are a Series B company backed by top investors, seeking individuals who thrive in startup environments, can prioritize independently, and are willing to take calculated risks to help pave the path forward.

NVIDIA is seeking an outstanding individual to join our platform SWQA team as a Platform Software Validation Engineer (SDET). This role involves developing and executing test plans for NVIDIA HGX/DGX/MGX platforms, covering servers, OS, firmware, and CUDA software stacks. You will be responsible for installing and testing various systems, OS, server firmware, and software stacks, and driving root cause analysis for reliability and validation test failures. The position requires building and developing server and OS level automation frameworks and tests, reviewing partner and supplier test results, and managing the bug lifecycle within an agile development team.

$140k - $270k

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.

Eventual is building data curation for Physical AI, processing petabyte-scale video and sensor data to extract signals about how hands and objects interact, temporal events, and clip reliability for training frontier models. We are a small, well-backed team from leading tech companies, aiming to revolutionize how Physical AI models are trained by providing reliable, curated datasets derived from vast amounts of video footage. This role is based in our SF Mission District office, with a 4-day work week. As Technical Lead, Multimodal Research, you will drive the technical vision for Eventual's understanding of video data. You will own the strategy for selecting, prototyping, and deploying models and representations at scale, ensuring they meet rigorous evaluation standards and cost-efficiency targets. This is a senior individual contributor role focused on setting research direction and making key architectural decisions, while remaining hands-on with research and experimentation.

$150k - $300k

Innodata is seeking a Research Scientist to focus on the challenging area of video and multimodal AI models. This role involves partnering directly with customers and frontier labs to advance the science behind video understanding, video-language, and video-generation models. You will be instrumental in defining how data is designed, structured, and evaluated for these cutting-edge AI systems, ensuring that the data collected and the evaluations performed drive meaningful progress. Your work will directly influence the direction of research and development in this rapidly evolving field.

$160k - $185k

Innodata is a global data engineering company focused on the intersection of data and Artificial Intelligence (AI). Our mission is to enable the responsible advancement of AI by providing the data, evaluation frameworks, and human expertise needed to build trustworthy AI systems at scale. We offer a range of solutions, platforms, and services for Generative AI builders and adopters, leveraging over 36 years of experience in delivering high-quality data and outstanding customer outcomes. This role focuses on the science behind speech and audio models, addressing challenges in robustness across accents, noise, and code-switching, speaker diarization, speech naturalness, and streaming latency. You will be instrumental in building the data and evaluation designs that drive progress in these areas for customers and frontier labs. Your work will involve critical judgment on benchmark coverage, transcription conventions, and the appropriate use of automated versus human evaluation metrics. You will collaborate closely with our transcription and linguistics lead to ensure our data standards directly influence model learning.

$160k - $185k