Senior Product Manager (AI Experimentation Tooling)

Location: Hybrid role based in the New York City or San Francisco office, with an in-office expectation of two days per week.

Annual base salary: $160,000–$275,000 USD, plus discretionary bonus, equity, and benefits.

Company

hirify.global builds an end-to-end platform for developing, training, and deploying AI systems, combining developer-first software with large-scale AI compute.

What you will do

• Own the product vision, strategy, roadmap, launch, adoption, pricing, packaging, and go-to-market for experimentation and post-training products.
• Build coherent workflows for training jobs, experiment comparison, fine-tuning, reinforcement learning, model evaluation, failure analysis, and checkpoint selection.
• Define where to build differentiated experiences versus integrate with experiment trackers, evaluation frameworks, data tools, and model registries.
• Work directly with engineering on APIs, SDKs, execution systems, distributed workloads, observability, artifact management, and failure handling.
• Use evaluations and product metrics to guide roadmap decisions across activation, iteration speed, compute consumption, retention, and expansion.
• Support customer-facing and go-to-market work, including sales positioning, technical objection handling, and developer-facing content.

Requirements

• 7+ years of product management experience, including at least 3 years building infrastructure, platform, developer-tooling, or machine-learning products.
• Hands-on experience building products for ML engineers, AI researchers, or data scientists.
• Detailed knowledge of experimentation and post-training workflows, including training jobs, checkpoints, metrics, artifacts, reproducibility, experiment comparison, and model evaluation.
• Experience with supervised fine-tuning, preference optimization, reinforcement learning, distributed training, or hyperparameter optimization.
• Strong product and interaction judgment, technical depth, prioritization, communication, and end-to-end ownership.
• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.

Nice to have

• Experience at an AI infrastructure company, neocloud, hyperscaler ML platform, experiment-tracking company, or developer-tooling startup.
• Familiarity with PyTorch, PyTorch Lightning, distributed training, GPU infrastructure, or large-scale fine-tuning.
• Experience with Weights & Biases, MLflow, Hugging Face, Ray, Slurm, Kubernetes, or comparable ML platforms.
• Experience building collaborative workflows that move models from research through evaluation and production.

Culture & Benefits

• Hybrid work model with flexible schedules for office-based teams.
• Medical, dental, and vision coverage, including eligible dependents.
• Meaningful equity, U.S. 401(k) matching, and comprehensive paid leave.
• Unlimited PTO, company holidays, a two-week winter break, and paid parental and family leave.
• Annual professional development allowance, wellness and work-from-home stipends, and complimentary office meals.
• Four weeks of paid sabbatical leave after four years of service.