# Product Manager, Training Platform at Baseten > Hybrid · United States · Unspecified · Product · open. Source: https://alderhq.app/jobs/ashby%3Abaseten%3A0a6f7d46-a0c3-4020-a697-e1bf1a8aeafa (read 2026-11-11). ## Facts (observed) - Company: [Baseten](https://alderhq.app/companies/baseten) - Location text: San Francisco; New York - Where it can be done from (inferred): Hybrid · United States (evidence: "Location: San Francisco; New York") - Posted: 2026-11-11 (0 days ago) - First seen by alder: 2026-11-11 · last verified: 2026-11-11 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://jobs.ashbyhq.com/baseten/0a6f7d46-a0c3-4020-a697-e1bf1a8aeafa - Skills listed (inferred): Spark ## Pay and sponsorship - Posted pay: $200k–$400k per year (from the listing's pay field) - Market band for similar posted roles (SF Bay Area, n 256): p25 $168k, median $203k, p75 $251k ## Description (the employer's text) ### ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. ### PRODUCT AT BASETEN Baseten is building a new cloud for AI. Our ambition is to make inference, training, and agent execution part of one coherent platform, and to shape how the next generation of AI products gets built. Product decisions here reach from the economics of GPU infrastructure to the abstractions developers build on every day. We’re hiring builders and tastemakers with the ambition to help create that future. You should bring a strong point of view about what should exist, the taste to make complex technology feel simple, and the technical judgment to build it alongside engineers, researchers, and designers. You’ll work directly with customers and forward deployed teams, turn emerging capabilities into new possibilities for developers, and carry an idea from early conviction through to production and adoption. ### THE ROLE Help make training and fine-tuning AI models dramatically easier. Training a model is hard enough. Developers shouldn't have to spend their time wrestling with infrastructure, waiting for GPUs, or figuring out why a job failed. We're building a training platform that lets AI teams focus on improving their models instead of managing the systems underneath them. As Product Manager for Training Platform, you'll own the developer experience for running training jobs on Baseten, from environment setup and job submission to scheduling, debugging, checkpointing, and recovery. You'll work alongside engineers and researchers solving some of the hardest problems in distributed training, helping turn that complexity into a product developers can depend on. ### RESPONSIBILITIES Own the product experience for training jobs, from setup and submission through execution, monitoring, and recovery Make distributed training easier to use, with intuitive workflows for scheduling, GPU availability, logs, checkpoints, and debugging Work closely with research and infrastructure teams to support different training workloads, including supervised fine-tuning and reinforcement learning Help developers recover from failures, reproduce experiments, and spend less time waiting on infrastructure Connect training with the rest of Baseten's platform, including Loops, model evaluation, and inference deployment Work directly with customers to understand how they train and adapt models, then turn those insights into product improvements ### REQUIREMENTS Experience building and shipping AI/ML products or developer platforms A technical background in software engineering, ML engineering, research, or equivalent hands-on work Direct experience working with teams that train, fine-tune, or adapt machine learning models Strong understanding of distributed training concepts, including GPU memory, scheduling, data access, checkpointing, and fault recovery Familiarity with the infrastructure needs of supervised fine-tuning and reinforcement learning Strong product instincts for developer workflows and the ability to simplify technically complex systems Experience partnering with researchers and engineers to take new capabilities from concept to production ### NICE TO HAVE Hands-on experience running distributed training, building ML developer tools, or working with trainer and sampler systems for reinforcement learning. ### WHAT SUCCESS LOOKS LIKE AI teams can run more experiments, recover from failures faster, and spend more of their time improving models instead of managing compute. Baseten becomes a natural place to train, fine-tune, and deploy custom AI models. --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Abaseten%3A0a6f7d46-a0c3-4020-a697-e1bf1a8aeafa and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.