Product Manager, Training Platform

Baseten

. Own the product experience for training jobs, from setup and submission through execution, monitoring, and recovery .

Posted 11/11/2026full-timeUnited StatesMid-LevelSenior💰 $200,000 - $400,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and shipping AI/ML products, with a strong focus on distributed training concepts and developer workflows. Capable of collaborating with research and infrastructure teams to enhance product experiences and simplify complex systems.

Highest-signal resume keywords

AI/ML Product DevelopmentDistributed Training ConceptsGPU Memory ManagementSupervised Fine-TuningReinforcement Learning

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringML EngineeringModel EvaluationCheckpointingFault RecoveryExperiment ReproductionInfrastructure Needs AssessmentWorkflow SimplificationData Access ManagementDebugging

Soft Skills

Product InstinctsCollaborationCustomer UnderstandingAdaptability

Industry Keywords

Training JobsDeveloper PlatformsIntuitive WorkflowsMonitoringExecutionProduct Improvements

About the role

Key responsibilities & impact

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 supervised fine-tuning and reinforcement learning workloads
Help developers recover from failures, reproduce experiments, and spend less time waiting on infrastructure
Connect training with 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

What you’ll need

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

Benefits

Comp & perks

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