Reinforcement Learning Jobs

Ambral Labs is building a platform to help enterprises leverage their historical data to improve AI model performance. The system reconstructs past company workflows into replayable environments, allowing for the evaluation and enhancement of agent behavior through reinforcement learning and other post-training techniques. This enables companies to develop better, more cost-efficient AI models that they own and control, rather than relying on third-party providers. Having graduated from YC and secured significant funding, Ambral Labs is now expanding its founding team.

$165k - $325k

Labelbox is building the critical infrastructure for breakthrough AI models, focusing on data-centric approaches. We offer integrated solutions for frontier AI development, including an Enterprise Platform & Tools for scalable data annotation, a Frontier Data Labeling Service with specialized expertise, and an Expert Marketplace connecting AI teams with skilled annotators. We operate in a high-impact, fast-paced environment that rewards ownership, technical excellence, and continuous learning. This role is central to advancing frontier agent capabilities, bridging the gap between training and infrastructure by building the systems that run experiments, including environments, verifiers, and fine-tuning pipelines. We seek engineers with strong judgment who can set technical direction, build reliable systems quickly, and are at the forefront of agent-first engineering practices.

$250k - $280k

Alignerr, Labelbox's human data organization, is seeking a Forward Deployed Research Scientist to join their team. This role sits at the intersection of research science and client delivery, embedding research capability directly into client engagements. Unlike traditional research roles, you will work on multiple client projects simultaneously, operating on short timescales of days to weeks. You will engage with research teams at major AI labs, reason scientifically about data strategy in real time, fine-tune open-weight models to validate data methodology, and collaborate with the Applied Research team on publications. This fast-paced, applied role offers clear ownership and autonomy, with career growth directly tied to your contributions.

$200k - $300k

Labelbox is seeking a Forward Deployed Engineer to design, develop, and operationalize reinforcement learning (RL) environments. This role involves building sandboxed, reproducible execution environments for AI agents during training and evaluation, such as terminal-based task benchmarks, browser environments, and tool-augmented workspaces. You will write production-quality infrastructure code, integrate with open-source RL tooling, and collaborate with the data operations team to ensure environments are robust and observable. While not a research role, a deep understanding of how RL training loops consume environments and identify bottlenecks is essential.

$140k - $200k

Thinking Machines is seeking a Site Reliability Engineer (SRE) to ensure the speed, reliability, and ease of iteration for our post-training and reinforcement learning (RL) systems. This role is akin to production engineering or site reliability, focused on model training infrastructure. You will be responsible for the health of training runs, clusters, and pipelines, working closely with research teams to debug issues in real-time, strengthen infrastructure, and develop tools and automation that allow researchers to focus on scientific discovery rather than job management. This position offers significant ownership, requiring you to be the point person for critical issues during active model runs and to implement solutions preventing future occurrences.

$300k - $350k

NVIDIA is seeking a motivated Deep Learning engineer to integrate advanced CUDA features and Distributed Runtime technologies into AI stacks, including frameworks like PyTorch, TRT-LLM, vLLM, SGLang, and JAX. You will join the team responsible for core CUDA features and runtimes that scale Deep Learning and HPC applications, addressing diverse multi-GPU demands from large-scale training to low-latency inference. Your work will enhance the productivity and performance of AI applications, accelerating community adoption through AI toolkits. This role offers a significant opportunity to advance the state of the art in AI technologies.

$184k - $357k