RL Jobs

Together AI

This research engineering role focuses on translating new Reinforcement Learning (RL) algorithms, scheduling methods, and inference optimizations into production-grade systems that power Together's API. The Core ML team operates at the intersection of efficient inference (algorithms, architectures, engines) and post-training/RL systems, building and maintaining high-performance inference and RL engines at production scale. The goal is to significantly improve model speed, cost-efficiency, and capabilities through RL-based post-training. This position requires a blend of algorithmic understanding and systems engineering, with opportunities to work across the entire stack from RL algorithms and training engines to kernels and serving systems, ultimately driving measurable improvements in latency, throughput, cost, and model quality at scale.

$200k - $280k

Scale AI

The Enterprise ML team is at the forefront of the AI revolution, collaborating with customers to solve significant business challenges and develop advanced AI systems. This role involves leading a team of research scientists and engineers, shaping the research agenda, and overseeing the entire development lifecycle from prototyping to deployment. The ideal candidate is a leader comfortable with ambiguity, possessing a deep understanding of generative AI capabilities and limitations, and driven to transform research into robust, production-ready systems. You will mentor and grow a team, define a multi-year research roadmap, and foster an inclusive, high-performing culture.

$290k - $362k

Scale AI

Scale is seeking a Machine Learning Research Engineer to join the Agent Data Foundation team within the Enterprise ML Research Lab. This role will focus on defining and building the data flywheel that drives AI development, particularly for complex agents in enterprise settings. You will conduct cutting-edge research in areas such as synthetic data generation for RL post-training, building agents for production trace analysis, and contributing to a framework for agent construction. The goal is to create state-of-the-art agents through advanced post-training and agent-building algorithms, shaping the future of the GenAI movement.

$265k - $331k

Scale AI

This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate these advancements into real-world, scalable solutions.

$302k - $378k