Deep Learning Jobs

Scale AI

Scale AI is seeking a Technical Lead Manager for its Physical AI team, focusing on the development of general AI that can reason and act in the physical world. This role bridges cutting-edge Machine Learning research with physical robot deployment, leading a team of Research Engineers while remaining a hands-on technical contributor. The primary focus is on developing and evaluating Large-Scale Foundation Models, such as VLAs and World models, to enable robots and autonomous vehicles to generalize across diverse tasks and environments. The team leverages Scale's extensive data infrastructure to help build Foundation Models for Physical AI, aiming to redefine the future of automation.

$249k - $311k

Scale AI

Scale's Global Public Sector team is seeking Applied AI Engineers to build custom, end-to-end AI applications for public sector clients worldwide. This role involves leveraging the latest AI advancements to create impactful solutions, generate high-quality training data for national LLMs, and contribute to upskilling initiatives. You will work on developing and fine-tuning sophisticated models for real-world use cases, aiming to transform public sector operations and enhance citizen services through cutting-edge technology. Join a rapidly expanding team dedicated to shaping the future of AI in the public sector.

Poolside is building a company to create Artificial General Intelligence, aiming to accelerate software development through agentic systems, coding assistants, and frontier models. This role focuses on improving the quality of pretraining datasets for our models. You will leverage your experience and conduct training experiments to enhance dataset quality, including synthetic data generation and data mix optimization. Collaboration with Pretraining, Posttraining, Evals, and Product teams is essential to define data needs that address missing model capabilities and downstream use cases. Staying current with research in dataset design and pretraining is crucial, as you will lead original research initiatives and deploy technical engineering solutions into production, utilizing a performant distributed data pipeline and a large GPU cluster.

Scale AI

Scale works with leading AI labs to accelerate progress in GenAI research, focusing on optimizing data curation and evaluation to enhance LLM capabilities in text and multimodal modalities. This role involves developing novel methods to improve the alignment and generalization of large-scale generative models, collaborating with researchers and engineers on best practices in data-driven AI development, and providing technical and strategic input to foundation model labs for the next generation of AI models.

$252k - $315k

Scale AI

The Human Frontier Collective (HFC) Fellowship is a fully remote, six-month independent contractor opportunity designed to bring together top researchers and domain experts to collaborate on high-impact AI projects. Fellows will apply their expertise to design, evaluate, and interpret advanced generative AI systems, gaining exposure to cutting-edge research and working with an interdisciplinary network of leading thinkers. This role offers a flexible schedule with 10-40 hour work weeks and competitive pay based on project scope and skillset. Candidates must be authorized to work in the United States, as visa sponsorship is not provided.

Scale AI

The Human Frontier Collective (HFC) Fellowship is a program that brings together top researchers and domain experts to collaborate on high-impact AI projects. As an HFC Fellow, you will apply your expertise to design, evaluate, and interpret advanced generative AI systems, gaining exposure to cutting-edge research and working with a diverse network of leading thinkers. This is a fully remote, independent contractor opportunity with a flexible schedule, offering a chance to contribute to influential ML projects, co-author research publications, and develop your AI expertise within a supportive community.

Scale AI

The Human Frontier Collective (HFC) Fellowship is a six-month, fully remote, independent contractor opportunity designed to bring together top researchers and domain experts to collaborate on high-impact AI projects. Fellows will apply their expertise to design, evaluate, and interpret advanced generative AI systems, gaining exposure to cutting-edge research and working with an interdisciplinary network of leading thinkers. This role offers a flexible schedule, allowing fellows to set their own hours (10-40 hours per week), and provides opportunities for professional development through review projects, advisory roles, and research, contributing to academic visibility and professional recognition.

Google DeepMind

Google DeepMind's research team is dedicated to tackling complex challenges in online information quality, advancing the state of the art by developing innovative solutions to detect manipulated media and misleading narratives. The team leverages interdisciplinary work spanning provenance analysis and the creation of tools for AI-assisted information literacy, with a focus on ensuring the integrity of digital discourse and a safer online environment. This role involves researching and building multimodal reasoning systems and Vision-Language Models (VLMs) to assess the trustworthiness of media on the internet, with a passion for advancing information literacy using machine learning and computational techniques.

thinkingmachines

Thinking Machines Lab is seeking pre-training researchers to join their mission of advancing collaborative general intelligence. This role is central to developing the next generation of AI models by blending research with large-scale data engineering. You will be responsible for assembling pre-training datasets and data systems, designing and implementing methods for sourcing, curating, and analyzing data for quality and performance. The position involves working with automated pipelines and human-in-the-loop processes, contributing both scientific insights and production-grade code. It's an ideal opportunity for individuals passionate about the intersection of data, machine learning, and systems, and who are eager to shape the future of AI.

$350k - $475k

thinkingmachines

Thinking Machines Lab is seeking an infrastructure research engineer to design and build core systems for efficient large-scale model training, with a specific focus on numerics. This role involves enhancing the numerical foundations of their distributed training stack, optimizing precision formats, kernel optimizations, and communication frameworks to ensure stable, scalable, and fast training of trillion-parameter models. The ideal candidate will bridge research and systems engineering, possessing a strong understanding of both optimization mathematics and distributed compute realities.

$350k - $475k

thinkingmachines

Thinking Machines Lab is seeking an infrastructure research engineer to design, optimize, and maintain the compute foundations for large-scale language model training. This role involves developing high-performance ML kernels, enabling efficient low-precision arithmetic, and improving the distributed compute stack. You will work closely with researchers and systems architects, bridging algorithmic design with hardware efficiency, prototyping new kernel implementations, and defining numerical and parallelism strategies for scaling AI systems.

$350k - $475k

Mistral AI

Mistral AI is seeking an Applied Scientist with deep expertise in engineering sciences to work at the forefront of AI-accelerated simulation. This role involves collaborating with industrial customers and internal research teams to build and deploy AI Physics Models, complementing our existing Large Language Models (LLMs). You will be involved in the entire process, from curating high-fidelity simulation datasets and training/evaluating models to delivering production-grade AI solutions directly to engineering teams. The target domains include computational fluid dynamics, structural mechanics, semiconductor design, multi-physics modeling, and digital twins. Working cross-functionally, you will ensure our models meet stringent engineering standards beyond just benchmark metrics.

Abridge

Abridge is seeking Clinician Scientists to advance the development of its AI-powered clinical tools. This role requires a blend of deep clinical expertise and a background in AI, focusing on shaping AI-driven tools to ensure accuracy and quality for clinicians and patients. You will collaborate closely with engineers, researchers, product managers, and fellow clinicians to refine AI models, validate outputs, and create new functionalities that enhance documentation workflows.

Poolside is building a company to create Artificial General Intelligence, aiming to accelerate software development through agentic systems, coding assistants, and frontier models. This role is part of the Applied Research team, focused on transforming pre-trained Large Language Models (LLMs) into well-aligned and highly capable AI systems specifically for coding and software development. You will be involved in building data pipelines and environments for agentic use cases, researching and implementing post-training algorithms, and designing experiments to test hypotheses, with access to significant GPU resources.

Mistral AI

Mistral AI is seeking an Applied AI Engineer to join their team and facilitate the adoption of their products among customers. This role involves collaborating closely with clients from pre-sale to post-implementation, ensuring their solutions meet and exceed expectations. You will manage daily customer relations, acting as a key resource for externalizing research into production settings and driving the successful deployment of Mistral AI products. The position offers the opportunity to work on state-of-the-art Generative AI applications across various industries and contribute to a pioneering company shaping the future of AI.

Skild AI is seeking a Machine Learning Engineer to design and implement cutting-edge reinforcement learning algorithms for robotic applications. This role involves conducting experiments, optimizing models for real-world robotic environments, and collaborating with robotics, research, and engineering teams. The work will directly contribute to the development of intelligent, adaptable robots capable of autonomous learning and complex task performance.

Skild AI is building the world's first general-purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. We are seeking a Machine Learning Engineer to design and implement cutting-edge reinforcement learning algorithms for robotic applications. This role involves conducting experiments, optimizing models for real-world robotic environments, and collaborating closely with our robotics, research, and engineering teams. Your work will directly contribute to the development of intelligent, adaptable robots capable of autonomous learning and complex task performance.

Skild AI is seeking a Research Engineer to join our post-training team. In this role, you will be responsible for enhancing Skild's foundation models and deploying them onto robots in real-world scenarios. You will collaborate with customers and utilize deployment data to ensure reliable robot behavior, focusing on safety, efficiency, and robustness under operational constraints. This position bridges the gap between strong lab performance and dependable customer deployments, defining the standard for scaling autonomous systems into global infrastructure.

We are seeking an engineer to join our team responsible for building and running the inference engine behind Perplexity's queries. This role involves deploying dozens of model architectures at scale, managing tight latency and cost budgets, and working with a stack including Rust, Python, CUDA, and CuTe DSL. You will contribute to supporting new models, migrating GPU kernels, developing a Rust-native serving runtime, optimizing performance, and enhancing reliability and observability.

We are seeking an AI Inference Engineer to join our dynamic team. This role is central to Perplexity's operations, as you will build and manage the inference engine that powers every query. You will deploy a variety of model architectures at scale, focusing on meeting stringent latency and cost requirements. Our technology stack includes Rust, Python, CUDA, and the CuTe DSL.