Machine Learning Engineer – Post-Training, AI StudioAbout The AI StudioThe AI Studio's mission is to find the fastest possible path to an autonomous supply chain. We're developing AI agents, learning systems, training models, and more to overcome the biggest challenges remaining in the global supply chain.In short, we are having a lot of fun.Your mission in this roleWe're looking for an ambitious Machine Learning Engineer specializing in Post-Training to work on environments, evaluations, data pipelines, and tooling for robust training systems.Your work will directly impact how our agents learn to make decisions in complex supply chain environments. You'll help shape how we approach reward modeling, environment design, and agent training.This role blends research and engineering. You'll implement novel approaches and contribute to our research direction while shipping production-grade systems. If you're energized by pushing the boundaries of what's possible, this is your chance.ResponsibilitiesDesign and implement post-training environments for supply chain decision-making Create evaluation frameworks to measure agent performance and catch failure modes Build data pipelines for training and human feedback collection Optimize training infrastructure for throughput, efficiency, and fault tolerance Debug complex issues in training pipelines and model behavior Collaborate with the team to translate research ideas into reliable systems Document what works (and what doesn't) so we can compound our learnings Stay on top of industry trends and cutting edge use cases We want to talk if youHave trained or fine-tuned LLMs for agents with SFT/DPO Are proficient in Python, PyTorch and HF Transformers Can balance research exploration with shipping working code Are comfortable working with large datasets and building data pipelines at scale Thrive in fast-moving environments where priorities shift Are excited about AI-assisted tools and getting the most out of them Can balance research exploration with shipping working code Care about craft in your work Have a deep sense of curiosity and make a habit of learning Think globally about how your work impacts the entire organization Bonus points ifHave hands-on experience with RL techniques (reward shaping and design, PPO, GRPO and other RLHF approaches) Have experience with distributed training systems and techniques (DDP, FSDP, N-D parallelism) You have experience with human-in-the-loop ML systems You've built evaluation frameworks for open-ended tasks You're familiar with supply chain, logistics, or operations domains You have experience with Kubernetes and cloud infrastructure (AWS, GCP) You've worked on reward hacking detection or robustness problems You have a side project that shows you can't stop tinkering  Our ValuesIf you want to know the heart of a company, take a look at their values. Ours unite us. They are what drive our success – and the success of our customers. Does your heart beat like ours? Find out here: Core ValuesAll qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.