AI Research Engineer Jobs

Cartesia

Cartesia is pioneering AI architectures that learn and interact with the world like humans. We are seeking a Research Engineer, Data Infrastructure to build the datasets and systems essential for pretraining our foundational models. This role involves developing performant, scalable infrastructure for acquiring, processing, and curating massive datasets, and collaborating closely with research teams to optimize data composition. Your contributions will directly influence the capabilities and quality of our cutting-edge models.

$200k - $350k

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

Anthropic

Anthropic is dedicated to building reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society. This role focuses on Multi-Agent systems, which are increasingly vital for AI deployment, from small subagents within products to large groups tackling complex problems. Training Claude for optimal performance and safety in these large groups is a challenging new frontier in reinforcement learning and a new way to scale compute at test time.

$500k - $850k

Assort Health

Assort Health is building a continuous conversation for every patient, powered by an AI agent that remembers context and carries it through their healthcare journey. The company has developed a proprietary dataset of 285 million patient interactions and is experiencing rapid growth, having raised $222 million. As a Research Engineer, you will be responsible for developing industry-leading healthcare AI models and pipelines, taking them from concept to production. You will own significant initiatives to advance the capabilities of AI models and agents in healthcare, ensuring high levels of reliability, efficiency, and precision.

$190k - $240k

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

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

Together AI

As a Research Intern in the Model Shaping team, you will contribute to advanced post-training methods, explore new techniques for efficient neural network training, and work on robust evaluation of foundation model capabilities. The Model Shaping team focuses on tailoring open foundation models for downstream applications, developing services for model selection and improvement, and creating new methods for efficient model training and evaluation. This role offers the opportunity to work on cutting-edge research, potentially leading to publications in top-tier conferences.

$58k - $70k

Together AI

As a Research Intern in the Model Shaping team, you will contribute to advanced post-training methods, explore new techniques for efficient neural network training, and work on robust evaluation of foundation model capabilities. The Model Shaping team focuses on tailoring open foundation models for downstream applications, developing services for model selection and improvement, and creating new methods for efficient model training and evaluation. This role offers the opportunity to work on cutting-edge research, potentially leading to publications in top-tier conferences.

$58k - $70k

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.

Salary not listed

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.

Salary not listed

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.

Salary not listed

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.

Salary not listed

Together AI

Together AI's Model Shaping team focuses on tailoring open foundation models for downstream applications, building services that help ML developers select and improve models with domain-specific data. The team also develops efficient model training and evaluation methods, drawing from machine learning, NLP, and ML systems. As a Research Engineer, you will develop a platform for users to customize open-source models with their own data, working across training and inference stacks. You will build and enhance services for Fine-Tuning, Reinforcement Learning, and Evaluation, ensuring a smooth transition from post-training to production serving and optimizing inference engines for RL training. Collaboration with product, research, and engineering teams is key to maintaining API reliability and performance, ultimately contributing to the foundational layer of the open-source AI ecosystem.

$200k - $290k

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

Anthropic

Anthropic's mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society. The Vision team is seeking a research engineer to focus on visual and spatial reasoning as core capabilities for LLMs. This role involves owning the end-to-end process of creating training data and RL environments for visual knowledge work. You will identify tasks, build evaluations, design rewards, and scale data, combining applied research with hands-on data work. Collaboration with external vendors, pretraining, RL, and product teams is essential to ensure the environments built translate into real-world knowledge work capabilities.

$350k - $850k

Roboflow

Roboflow Labs is seeking a Research Scientist to join their applied research unit. This role sits at the intersection of benchmarks, models, and frontier labs, focusing on failure analysis, dataset specification, and validation of data quality. The scientist will contribute to publishing new benchmarks, extending existing ones like RF100-VL, and shaping the research agenda with work grounded in real-world deployments. This position offers the opportunity to see research directly translate into shipped data products and influence the direction of AI development.

$250k - $450k

Thinking Machines Lab

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

Databricks

Databricks AI Research is seeking a Principal Research Scientist – Scaling to lead a team focused on advancing the state of the art in large-scale machine learning, particularly in LLM training and inference efficiency. This role involves defining and executing a research roadmap to improve how customers train, serve, and adapt LLMs at scale, working closely with product, data, and engineering leaders. The goal is to push the boundaries of LLM efficiency beyond existing models, exploring novel algorithms, systems, and infrastructure improvements. You will drive independent research agendas and collaborate on low-level implementation details to bring cutting-edge methods into production and enhance the Databricks AI platform.

$280k - $350k

Databricks

Databricks AI is seeking a Principal AI Research Scientist to lead a team focused on advancing the state of the art in large-scale machine learning, particularly in LLM training and inference efficiency. This role involves defining and executing a research roadmap to improve how customers train, serve, and adapt LLMs at scale, working closely with product, data, and engineering leaders. The ideal candidate will drive algorithmic innovations, optimize ML systems for distributed training and inference, and translate research breakthroughs into customer-impacting capabilities within the Databricks AI platform. This position also requires fostering a culture of scientific excellence, representing Databricks AI externally, and mentoring research talent.

$270k - $340k

As a Research Scientist at Mercor, you will work at the intersection of research and engineering on frontier post-training. You will develop new training and evaluation methods, test them through rigorous experiments, and implement successful approaches at scale. Working with researchers, engineers, domain experts, and customers, you will investigate how data, rewards, environments, and optimization methods shape model behavior. Your work will influence frontier models, Mercor’s products, and the broader research community through releasing blogposts, technical reports, and papers.

$250k - $500k

As a Senior Research Engineer at Escape, you will join a team of talented security researchers focused on innovating and translating cutting-edge research into impactful production solutions. You will play a key role in developing agentic scanning systems that autonomously explore applications, designing and implementing a robust security detection engine for various vulnerabilities, and integrating AI, specifically LLMs, into scanning workflows to enhance coverage and accuracy. Your work will also involve building and optimizing distributed infrastructure for large-scale concurrent scans, ensuring performance and reliability, and contributing to core platform architecture decisions.

Salary not listed

Thinking Machines Lab

At Thinking Machines, we build tools that empower individuals to customize AI models for their specific needs, including the ability to train model weights. In this role, you will focus on frontier customization techniques and contribute to developing a leading post-training engine called Tinker. Your work will involve a comprehensive understanding of Reinforcement Learning (RL) science, and your findings will directly influence Tinker's training defaults, API design, and the open-source Tinker Cookbook. You will collaborate with internal research teams and contribute to open science initiatives for external partners.

$350k - $475k

Thinking Machines Lab

Thinking Machines is building AI that extends human will and judgment, with a focus on training frontier models and developing tools that allow users to customize AI for their unique needs. This role leads the Fine-tuning Science team, focusing on frontier customization techniques and the Tinker post-training engine. It's a player-coach position where you will remain hands-on with scientific research while also guiding the team, shaping its direction, and ensuring research findings are integrated into Tinker. You will collaborate with internal research teams, contribute to open science, and engage with external users.

$350k - $475k

Cursor

As a Research Engineer on the Synth Data team at SpaceXAI, you will invent and scale the synthetic data that teaches our models new capabilities. You will own the full loop: spotting a capability the model is missing, designing a data generation strategy, building reliable pipelines and verifiers, and validating that the resulting data actually moves the model. You will form hypotheses about what data will help, build the systems to produce it at scale, run ablations, and read the resulting traces and training signals to understand why it worked (or didn’t). Your datasets will go directly into frontier training runs and shape the development of Grok models.

Salary not listed