Reinforcement Learning Jobs

Together AI

Together is seeking a Senior Product Engineer to join their central Product Engineering team, working closely with the Commerce engineering team. You will be responsible for the product UI for Together AI's critical user flows, including enterprise spend controls, governance, usage-based pricing, metering dashboards, payment management, and enterprise contract interfaces. This role requires a hands-on individual who can efficiently break down ambiguous tasks, deliver improvements quickly, and make pragmatic decisions to drive customer and revenue impact. You will collaborate with product, design, and backend engineers, leveraging strong product judgment to make UX decisions within established patterns.

$160k - $230k

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

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

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

As a Customer Success Engineer at Together AI, you will be the named technical owner for one of our most strategic customer relationships. You will serve as the primary technical point of contact across all infrastructure domains, including compute, networking, storage, and facilities, ensuring the flawless delivery and operational health of large-scale GPU deployments. This role is crucial for driving both customer success and company growth by combining deep infrastructure expertise with high-stakes customer partnerships.

$260k - $290k

Faire is a technology wholesale platform connecting independent retailers globally. We leverage AI and machine learning to empower local businesses to compete effectively. This role focuses on the Retailer Growth Data team, developing AI/ML systems for paid marketing and top-of-funnel acquisition. Opportunities include optimizing bidding, keyword intelligence, audience targeting, and incrementality estimation. There's a significant chance to explore AI/ML and LLMs for programmatic content creation, reinforcement learning, and landing page optimization to drive growth.

$211k - $291k

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

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

Labelbox is seeking a Member of Technical Staff to lead the design, development, and production of Frontier Data Products. This role involves building the essential sandboxed, reproducible environments that AI agents require for training and evaluation, including terminals, browsers, and tool-augmented workspaces. You will be responsible for writing production-quality infrastructure, integrating with the RL tooling ecosystem, and ensuring environments are robust and observable. A strong understanding of how RL training loops consume environments and potential failure points is crucial.

$140k - $200k

Snorkel AI is seeking a Forward Deployed Engineer specializing in Synthetic Data Generation to collaborate with leading AI labs and enterprises on critical AI initiatives. In this role, you will spearhead the technical execution of complex customer projects that leverage synthetic data to enhance model training, evaluation, and overall performance. You will be responsible for transforming vague model and data challenges into concrete data strategies, developing robust generation and evaluation pipelines, and utilizing experimentation to continuously improve data quality and downstream model results. Your work will span the entire delivery lifecycle, from initial technical discovery and solution design to implementation, evaluation, and production deployment. Additionally, you will identify common patterns across engagements to develop reusable capabilities, technical standards, and product enhancements.

$180k - $320k

Snorkel AI is seeking a Forward Deployed Engineer specializing in Computer Use Agents (CUA) to collaborate with leading AI organizations on their critical agentic AI projects. This role involves leading the technical execution of complex customer engagements focused on agents that interact with computers, browsers, and software to accomplish multi-step tasks. You will translate challenging product and model issues into effective task environments, datasets, and evaluation strategies to enhance agent reliability and overall performance. The position spans the entire delivery lifecycle, from initial technical discovery and solution design to implementation, evaluation, and production deployment. Additionally, you will identify common patterns across projects to develop reusable capabilities, technical standards, and product enhancements.

$180k - $320k

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 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

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

Applied Intuition is building a robot learning platform to enable any robot to learn industrial tasks and continuously improve. The robotics team develops this platform and uses it to deliver robot autonomy on customer lines, training, evaluating, and deploying policies on real robots performing industrial tasks. This role involves hands-on work with hardware, seeing your contributions reach customers, and working on manipulation policies from task definition to reliable execution on a physical robot. You will train and fine-tune policies, diagnose failures, and ensure their dependability for customer use, with success measured on the robot itself.

$150k - $300k

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