We are seeking a talented and experienced product manager to define and execute the strategy for Forge, our product that enables customers to build, fine-tune, and deploy custom AI models at scale.
Forge turns cutting-edge research into enterprise-ready capabilities by powering model fine-tuning, reinforcement learning, and post-training workflows. By working at the intersection of research and product, it provides customers with the tools to train specialized models that deliver real-world business value.
As the PM leading Forge, you will shape a 0-1 product with significant business impact and the potential to grow, offering while defining how organizations train and deploy the next generation of AI models.
Define the Future
- Set the vision: Shape and evangelize a compelling product strategy for Forge, ensuring alignment with company goals and market opportunities.
- Spot the gaps: Lead market and UX research to uncover unmet needs, competitive whitespaces, and emerging trends in SOTA AI post-training capabilities.
Build & Ship
- Own the lifecycle: Drive end-to-end product development, from ideation to launch and iteration,balancing speed, quality, and user delight.
- Champion the user: Partner with design and research to craft intuitive, high-impact experiences, using data and feedback to refine continuously.
Scale, Execute, & Enable
- Go-to-market: Collaborate with marketing and sales to launch products successfully, including pricing, positioning, and adoption strategies.
- Align stakeholders: Rally engineering, design, and business teams around priorities, trade-offs, and timelines.
- Prioritize ruthlessly: Maintain a dynamic roadmap that delivers quick wins while advancing long-term bets.
Required Qualifications
- Product Management Experience: 5+ years of relevant experience in new, competitive, fast-paced, and ambiguous environments with a track record of building and scaling complex AI/ML or infrastructure solutions.
- Technical skills: Very good understanding of training pipelines, RL loops, and model deployment architectures,
- Expertise in AI model lifecycle management, including fine-tuning, evaluation, and serving.
- Experience with Infrastructure as Code (IaC), containerization, and scalable deployment modes (e.g., on-prem, VPC, cloud).
- Familiarity with Kubernetes/Slurm is a strong plus.
User obsession: Relentless focus on solving real user problems, backed by data and qualitative insights. Cross-functional influence: Proven ability to align and inspire engineering, design, and go-to-market teams without direct authority. Problem-solving: Balance big-picture thinking with hands-on problem-solving, you’re equally comfortable crafting a roadmap, diving into metrics, and running technical tests. Communication: Crisp, persuasive storytelling for executives, teams, and users,ability to distill complex technical concepts (e.g., RL, LoRA, SFT) into clear narratives for docs, decks, and workshops. Adaptability: Thrive in high-velocity, dynamic settings where priorities shift quickly. Collaboration: Low ego + high EQ,you build trust and drive decisions through clarity, not hierarchy. Autonomy: Self-directed with a bias for action, you own outcomes end-to-end.
Now, it would be ideal if you have:
- Infrastructure knowledge: Strong knowledge of model training, model architectures, etc.
- Strong understanding how complex architectures are designed and impact of deployment modes
- Proficient coding skills are strongly recommended
- Kubernetes know-how strongly recommended
- Growth mindset: Deep familiarity with product-led growth strategies (e.g., viral loops, onboarding optimization, monetization, etc.)
- Builder’s mindset: Founder or early-stage PM experience,you’ve turned 0 → 1 ideas into products users love.
- Technical depth: Ability to prototype, hack, or dive into code when needed.
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