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Open nowPosted 6 hours ago

Product Manager, Training Platform

Baseten103 open roles

Pay
$200,000 – $400,000 a year
Where
San Francisco
Work mode
Hybrid
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Your applicationOpen nowProduct Manager, Training PlatformBaseten · San Francisco

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

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The clock on this job

Early applications get read.

13.8% of postings close within 7 days. Measured by our own scanner across the market. Baseten postings stay open a median of 59 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 13.8%7 days
  4. 22.3%14 days
  5. 37.8%30 days
  6. 59.0%60 days
This job: posted 6 hours ago

Baseten median: 59 days open

The posting

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 https://www.baseten.co/blog/announcing-our-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.

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 (our offices are closed from Christmas Eve to New Year's Day!)

- 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.

Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.

At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.

We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

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