About Us
We are a well-funded, early-stage AI lab focused on building the next generation of frontier multimodal AI models. Founded by former DeepMind researchers, including Andrew Dai, who was previously a leader on Gemini. Our team currently consists of 20 world-class scientists and engineers. We raised $55M in seed funding from Striker Ventures, Menlo Ventures, Altimeter Capital, and NVIDIA. We are tackling some of the hardest problems in artificial intelligence, and we are growing fast.
About the role
Product leadership at Elorian AI sits directly at the intersection of breakthrough research, hardcore systems engineering, and rapid enterprise adoption. Based in our Palo Alto office, this role is built for a high-judgment operator who demands true ownership across the entire model lifecycle—from early training priorities to production deployment and iterative refinement.
As our founding PM, you will take full end-to-end command: scaling our public API, architecting the launch of our next-generation frontier foundation models, and steering the pivotal strategic tradeoffs between broad developer infrastructure and high-value vertical solutions.
What you will do
Own the Business & Product Roadmap End-to-End
Drive the Frontier AI Roadmap: Take full ownership of the product lifecycle—optimizing our existing public API today while architecting the release strategy and developer experience for our upcoming frontier foundation models.
Shape the Strategic Trajectory: Evaluate and prioritize high-stakes business bets: steer the balance between expanding a broad horizontal developer platform and building high-impact vertical applications.
Run the Release Tempo: Own pre-training and fine-tuning priorities from a product lens, driving alignment, evaluation, and rapid iterative deployment.
Bridge Research, Engineering, and Go-to-Market (GTM)
Single Source of Truth: Serve as the central conduit connecting customer-facing commercial teams with world-class research scientists and core infrastructure engineers.
Turn Breakthroughs into Products: Translate state-of-the-art multimodal research capabilities into intuitive, scalable developer primitives and production features.
Market-Driven Sprints: Align engineering sprint priorities and compute resources with clear enterprise customer demand and real-world adoption signals.
Partner with GTM to Drive Enterprise Adoption & Revenue
Abstract Customer Insights: Partner closely with GTM leadership to systematically capture user pain points, workflow bottlenecks, and enterprise feedback from early design partners.
Monetization & Expansion: Convert early market signals into high-converting product features, tiered enterprise offerings, and sustainable monetization mechanisms.
Customer-Facing Impact: Join key customer conversations to uncover novel use cases, prototype solutions, and establish repeatable enterprise playbooks.
Define Developer Experience & UX Beyond the API
Full-Stack Product Experience: Elevate our product by shaping an exceptional end-to-end developer journey.
Evaluation Flywheels & Quality: Partner with research to build automated data flywheels and closed-loop feedback systems that turn edge cases and real-world usage into model benchmark gains.
Balance the AI Trilemma: Make sound first-principles tradeoffs between model intelligence, inference latency, serving cost, and safety.
What we are looking for
Relevant Experience: 5+ years of product management experience, with a proven track record of owning ML products or model development lifecycles from concept to launch.
True 0-to-1 Ownership: Demonstrated ability to operate as a sole or founding PM, navigating extreme ambiguity, setting up initial product workflows, and driving execution directly with research scientists and core engineers.
Data & Systems Rigor: Strong technical and analytical mindset with hands-on experience in model evaluation design, benchmark creation, data flywheels, and tracking performance metrics (proficiency in Python and SQL preferred).
First-Principles Thinking: Ability to make fast, sound prioritization decisions when balancing model quality, inference speed, compute costs, and safety without relying on existing playbooks.
Technical Communication: Ability to earn technical trust with research and engineering teams, translating complex model capabilities into clear product priorities and executable roadmaps.
Nice to have
Multimodal & Frontier Modeling Experience: Specific background working across multimodal models, frontier AI research, generative architectures, or large-scale foundation model development.
Founding Team & Early-Stage Startup Context: Experience as a founding product manager, founding team member, or early employee at a fast-growing startup—or lead PM on a 0-to-1 incubation team.
Developer Platform & Infrastructure Context: Prior experience building APIs, SDKs, model serving infrastructure, or developer platforms.
Logistics
Location: Palo Alto, CA
Type: Full-time
Compensation: $250k – $400k + meaningful equity stake + full health/wellness benefits