Product Manager, Training

Own strategy, roadmap, and delivery for an AI model training product across API, UI, and CLI. The role partners with customers and technical teams and requires product management experience, strong technical depth, and familiarity with model fine-tuning, evaluation, and production inference.

About the job

Responsibilities

Own the roadmap, strategy, and success metrics for parts of the training product across API, UI, and CLI.
Work directly with AI-native startups and enterprises running training workloads; identify obstacles and turn recurring pain points into product capabilities.
Convert bespoke work from forward-deployed and applied ML teams into scalable, self-serve products.
Partner with product marketing, sales, and field teams to launch training capabilities, including pricing and packaging, documentation, cookbooks, and enablement.

Requirements

2–8+ years of product management experience building technical or developer-facing products.
Strong technical background, such as a CS/EE degree, production engineering experience, or equivalent expertise.
Familiarity with the post-training lifecycle, including dataset curation, supervised fine-tuning (SFT), LoRA/PEFT, reinforcement-learning methods, evaluation, and production inference.
Demonstrated end-to-end ownership of a product area, from strategy and specifications through launch and metrics.
Excellent written communication for specifications, launch posts, and customer-facing technical explanations.
Comfort with ambiguity and a bias toward shipping and learning.
High motivation and willingness to work intensely when required.

Nice-to-haves

Personal experience fine-tuning models and deploying the results.
Experience with ML platforms, MLOps, or AI infrastructure products, including training platforms, evaluation tooling, or model registries.
Familiarity with reinforcement fine-tuning, reward modeling, rollout environments, and agent-training workflows.
Understanding of GPU economics and trade-offs among training cost, throughput, and quality.
Open-source or developer-community experience, especially with SDK and API usability.
Early-stage startup or founding experience.

Compensation and Benefits

Salary range: $170,000–$300,000.
Work on AI infrastructure and model training challenges with a high-impact, collaborative team.
Collaborate with engineers and AI researchers on emerging technologies.

Skills

Product Management, Machine Learning, MLOps, AI Infrastructure, Dataset Curation, Supervised Fine-Tuning, Lora, Peft, Reinforcement Learning, Model Evaluation, Model Registries, Gpu Economics, APIs, Cli, SDKs