8+ years of experience in machine learning or applied research, or a PhD with 4+ years of relevant industry experience
Demonstrated success developing LLM training methods or systems that produce meaningful improvements on real-world tasks
Deep expertise in LLM post-training, including supervised fine-tuning, reinforcement learning, on-policy distillation, reward modeling, and policy optimization
Strong research judgment, including the ability to identify high-impact problems, design rigorous experiments, and make decisions from ambiguous results
Experience taking research ideas from initial hypothesis through implementation, evaluation, and production deployment
Proven ability to set technical direction, lead complex cross functional initiatives, and mentor other engineers
Publications, open source contributions, or other demonstrated research impact in reinforcement learning, LLM post-training, or agent learning
Deep experience with distributed training, GPU optimization, and large-scale model training systems
We strive to use the best tool for the job when building and deploying our production services. Sometimes that means writing our own custom code, and often it means leaning on the work of others. As part of building Serverless RL, we depend on the following libraries and frameworks (among many others)
We work hard, have fun, and move fast! We’re in an exciting stage of hypergrowth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values
We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for takeoff, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!