Product Manager, Training Platform

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

Benefits

Competitive compensation, including meaningful equity; (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents; Flexible PTO policy including company wide Winter Break; Paid parental leave; Fertility and family-building stipend through Carrot; (U.S. only) Company-facilitated 401(k); Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities