PyTorch Jobs

Innodata is seeking a Research Scientist to lead the science of data for robotics foundation models. This role involves partnering directly with customers and frontier labs to define how data is designed, structured, and evaluated for next-generation AI systems in robotics. You will leverage scientific judgment to make high-leverage decisions about data capture, synthesis, representation, and evaluation, ensuring that the data collected and generated directly supports the development of robust and transferable AI models for manipulation, locomotion, vision-language-action, and world models.

$160k - $185k

Join Tenstorrent’s AI Models team and work at the layer most ML engineers never see: bringing advanced models to life on custom AI hardware. You’ll own real workloads end‑to‑end including porting, tuning, and validating LLMs and vision models on our accelerator, and chasing down every last millisecond and percentage point of accuracy. This role is for people who love the craft of ML engineering and want their work to matter at silicon scale, not just behind another API. This role is hybrid, based in Cyprus. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.

Tenstorrent is seeking a Physical Design Engineer to lead cross-functional efforts in solving complex physical design challenges and developing end-to-end RTL-to-GDS methodologies across advanced nodes, with a strong focus on PPA and runtime improvements. The engineer will architect, integrate, and deploy AI/ML-driven solutions into production physical design flows, creating custom CAD tools and partnering with internal teams and EDA vendors to drive next-generation, ML-enabled capabilities. This role is hybrid, based out of Santa Clara, CA or Austin, TX or Fort Collins, CO. We welcome candidates at various experience levels for this role, and offers will align with the assessed level.

$100k - $500k

Ramp is seeking a Machine Learning Engineer to lead the future of fraud machine learning. In this role, you will build core machine learning models, design data architectures, and set strategic roadmaps to mitigate fraud-related threats while minimizing friction for legitimate users. You will partner closely with product and engineering teams on model design, implementation, execution, and analysis. This is an opportunity to build systems that directly shape how companies move and manage billions.

$200k - $330k

Cerebras is developing a new generation of disaggregated AI inference systems that combine GPU-accelerated prefill with ultra-fast decode on the Cerebras Wafer-Scale Engine. We are seeking a Software Engineer to build and enhance the ML API layer, making this heterogeneous serving system accessible, reliable, and user-friendly. You will operate across our inference APIs, model integration layer, request-routing services, and the Cerebras inference platform to ensure a consistent experience across various models and accelerator backends. This role is at the intersection of machine learning systems, API design, model serving, and distributed systems, enabling new model architectures and inference capabilities while defining stable user-facing behavior and ensuring features like streaming, sampling, tool use, structured outputs, and multimodal inputs function correctly in production.

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.

Together AI

The Model Shaping team at Together AI focuses on tailoring open foundation models for downstream applications, building services that help machine learning developers select and improve models with domain-specific data. We also develop novel methods for efficient model training and evaluation, drawing from machine learning, natural language processing, and ML systems. As a Research Engineer on the Scaling Team, you will translate cutting-edge research in efficient foundation model training into robust, high-performance systems. You will optimize Together's training infrastructure, identify performance bottlenecks, and implement state-of-the-art techniques in production environments. Your work will directly influence the fine-tuning experience for Together's customers. You will integrate newly released open-source models onto the platform, ensuring efficient and reliable training across diverse workloads. Collaborating with Research Scientists, you will build experimental infrastructure to accelerate research and deploy validated ideas at scale.

$200k - $290k

Together AI

Together AI is building the best inference infrastructure for voice applications, powering production-grade, real-time voice agents and applications with best-in-class latency and reliability for speech-to-text and text-to-speech models. We are seeking a Staff ML Engineer to lead the model serving layer for voice workloads. This role involves hands-on optimization of inference engines and models, profiling GPU utilization, designing batching strategies for streaming audio, and ensuring rapid deployment of new model architectures from research to production. This is a foundational hire on a small, high-impact team, addressing the unique challenges of voice inference such as streaming audio, tokenization, and real-time latency budgets, and shaping the future of voice model serving.

$220k - $280k

Together AI

Together AI is building the best inference infrastructure for voice applications, powering real-time voice agents and applications with best-in-class latency and reliability for speech-to-text and text-to-speech models. We are seeking a Senior ML Engineer to lead the model serving layer for voice workloads. You will optimize inference engines like TRT-LLM and SGLang to serve models such as Whisper, Parakeet, Orpheus, and Kokoro, focusing on pushing latency and throughput boundaries. This role involves profiling GPU utilization, designing batching strategies for streaming audio, and accelerating the transition of new model architectures from research to production. As a foundational hire on a small, high-impact team, you will address the unique challenges of voice inference, including streaming audio, real-time latency, and tokenization, shaping how Together serves voice models as the industry moves towards end-to-end speech-to-speech systems.

$200k - $260k

Together AI

Together AI is seeking a Machine Learning Engineer to join our Inference Engine team, focusing on optimizing and enhancing the performance of our AI inference systems. This role involves working with state-of-the-art large language models and ensuring they run efficiently and effectively at scale. You will have the chance to collaborate closely with AI researchers and engineers to create cutting-edge AI solutions and shape the future of AI inference.

$200k - $300k

Perplexity is looking for an experienced Machine Learning Research Engineer to contribute to the development of next-generation advanced search technologies, with a particular emphasis on retrieval and ranking. This role involves architecting and building core components of the search platform and model stack, and deploying models from boosting algorithms to LLMs in a scalable and performant manner. The engineer will also be responsible for building and optimizing RAG pipelines for grounding and answer generation, and collaborating with cross-functional teams to ensure high-quality delivery.

Join our groundbreaking research team as we revolutionize the future of physical AI through advanced generative models. As a Research Scientist specializing in Generative AI for Physical AI, you will be at the forefront of developing next-generation algorithms that bridge the gap between virtual and physical realms. You will work with state-of-the-art technology and have access to massive computational resources to bring your ideas to life, shaping the future of AI where digital intelligence meets physical reality.

$168k - $265k

We are seeking a highly technical and strategic Senior Technical Lead to join our team, focusing on engaging developer ecosystems across emerging technology domains such as Generative AI, Autonomous Vehicles, and Simulation Platforms. You will work directly with software solution providers, developers, and industry professionals to foster the adoption of NVIDIA’s advanced AI and computing platforms. The ideal candidate brings a blend of deep technical expertise and commercial go-to-market experience, combined with a passion for developer advocacy and a talent for communicating how NVIDIA technology can solve complex, real-world challenges.

$224k - $357k

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

Handshake is seeking a Member of Technical Staff, Post-Training to help define and build a new organization focused on advancing the AI economy by organizing expert human knowledge. This role involves working directly with frontier labs on data, evaluation, and post-training challenges, building systems that transform expert knowledge into data and evaluations to improve frontier models. You will partner with researchers, domain experts, and customers to translate ambiguous post-training questions into experiments, evaluation frameworks, data pipelines, and products. As an early member, you will have significant influence over the technical direction, operating culture, and reusable systems built.

$200k - $350k