Senior Product Manager – Inference

Manage a Hybrid Inference Roadmap: Develop and execute a strategy for core prediction models that serves two distinct goals:

Productization into our core platform for the most high-usage use cases and
Tech-enabled-Service for internal teams to deliver bespoke predictions tocustomers. You will ruthlessly prioritize to ensure the core inference engineevolves to support both while minimizing forking.

Navigate Internal Complexity: Act as a diplomat and strategist within the will bring clarity to complex sometimes conflicting internal priorities drivingalignment between Engineering Science Go-to-Market and Product leadership.
Drive External Partnerships: Serve as the primary product interface for key partners helping to build and consume our predictions. You will translate partner scientific requirements into model capabilities manage expectations around prediction accuracy/confidence and ensure our technology creates value for them while remainingscalable for us.
Bridge the Gap (Science <> ML): Translate preclinical business objectives into technicaland data requirements. You will ensure that a single inference engine can effectivelyserve diverse use cases across the drug discovery pipeline (e.g. Target Identification Assessment vs. Study Design).
Measure Impact: Define and report on metrics that capture the value of the platformmoving beyond just model performance (F1 Precision/Recall) to demonstrate businessROI and scientific utility to diverse internal stakeholders.

5 years preferably 7 years as a Product Manager with increasing responsibility onAI/ML or Data Science product
Biopharma/Preclinical Fluency: You understand the drug discovery lifecycle (from Target ID to Lead Optimization). You can speak the language of scientists to understand the nuance of how a prediction helps or hinders their specific workflow. 2 years experience working in the Biotech or Pharma industry is a strong plus where you canbring a deep understanding of pre-clinical R&D to this role.
Experience with Probabilistic Products: You have successfully managed productswhere the core value is a prediction or inference. You know how to handle userexpectations around uncertainty confidence scores and false positives/negatives inhigh-stakes environments.
Experience in Technology-as-a-Service: A proven track record managing inferencetechnology that is consumed via API or service layer where that same technology powersinternal user-facing products.
Exceptional Stakeholder Management: You excel at navigating internal politics andorganizational dynamics. You have a history of driving consensus among strong-mindedresearch scientists and engineers without having direct authority.
Technical Fluency: Familiarity with LLMs Knowledge Graphs or predictive dont need to write code but you must be able to debate trade-offs (e.g. latency generalization vs. specificity) with engineering leads.
Strategic Resilience: You are comfortable with ambiguity and can make data-informeddecisions even when the path forward isnt obvious.