- Company Name
- Wise
- Job Title
- Senior Product Manager - Machine Learning and AI
- Job Description
-
**Job Title**
Senior Product Manager – Machine Learning and AI
**Role Summary**
Lead the design, launch, and scale of internal ML/GenAI platform tools that enable rapid, secure AI adoption across the organization. Bridge product vision with engineering execution, optimizing time‑to‑production, governance, cost, and performance while ensuring compliance and data privacy.
**Expectations**
- Own product roadmap and deliverables within the ML/GenAI domain.
- Drive high‑impact adoption by removing friction for cross‑functional teams.
- Balance speed with robust risk and privacy controls.
- Mentor and coordinate within multi‑disciplinary squads.
**Key Responsibilities**
- Identify and resolve adoption bottlenecks through data analysis, prototyping, and experimentation with Sagemaker, MLflow, Ray, or Bedrock.
- Prototype and validate feature roadmaps using SQL analytics, rapid prototyping, and A/B testing.
- Define success metrics, build dashboards, and report model performance versus business impact.
- Design and implement governance frameworks for experimentation, risk assessment, and privacy compliance.
- Collaborate with security to deploy model monitoring, access controls, and privacy safeguards.
- Develop cost‑optimization strategies that reduce ML infrastructure spend without limiting usage.
- Conduct vendor assessments and ROI analysis for AI tool selection.
- Define scalable architecture solutions (feature stores, multi‑cloud inference) in partnership with engineering.
- Build self‑service tools, documentation, and reusable components to enable 10× more teams to adopt AI.
**Required Skills**
- Proven experience as a technical product manager in AI/ML or data‑product roles.
- Strong technical fluency with ML pipelines, cloud services, and data engineering.
- Experience with SageMaker, MLflow, Ray, Bedrock, or equivalent platforms.
- Ability to craft governance and compliance frameworks for AI.
- Data‑driven decision making: SQL, analytics, dashboards.
- Excellent stakeholder communication, influencing, and cross‑functional collaboration.
- Familiarity with cost modeling and budget optimization for ML operations.
**Required Education & Certifications**
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.
- Relevant certifications (e.g., TensorFlow, AWS Certified ML, or similar) are a plus.