Senior PM, ML Platform & Personalization

Prime Video & Amazon MGM Studios

Seattle (WA)

In loco

USD 151.000 - 205.000

Tempo pieno

7 giorni fa

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Descrizione del lavoro

Amazon.com Services LLC is seeking a Senior Product Manager, Technical for Prime Video’s ML platform strategy. You will own a core set of capabilities across Data, ML, and Measurement platforms to enable teams to build, experiment, and productionize machine learning solutions at global scale.

Your mission is to remove bottlenecks across the ML lifecycle, from data ingestion to model training and deployment, aligning platform investments with customer personalization, content discovery, and

Competenze

2+ years of end to end product delivery experience.
5+ years of technical product or program management experience.
Bachelor's degree.
Experience contributing to engineering discussions around technology decisions and strategy related to a product.
Experience with feature delivery and tradeoffs of a product.
Experience owning/driving roadmap strategy and definition.
Experience managing technical products or online services.
Experience representing and advocating for a variety of critical customers and stakeholders during executive-level prioritization and planning.

Mansioni

Define and drive the roadmap for your area of the ML platform and infrastructure, articulating how platform decisions directly translate to customer-facing personalization outcomes across discovery, content intelligence, and emerging GenAI experiences.
Contribute to the data platform strategy, delivering clean, curated datasets that encode business logic and provide science teams with trusted, model-ready data foundations.
Build end-to-end ML tooling and pipelines that enable ML builders to discover datasets, ideate modeling approaches, conduct research and experimentation, and seamlessly productionize models from prototype to production.
Support large-scale model training, real-time inference, and compute optimization across CPU and GPU to ensure models perform efficiently at production scale.
Help evolve the feature store strategy, supporting both online and offline data serving while minimizing online/offline skew to ensure consistency between training and serving environments.
Own the developer experience for ML builders by delivering self-service tools, reusable components, and standardized workflows that increase productivity, reduce operational overhead, and improve cost efficiency, scalability, and availability.
Contribute to the measurement platform to monitor model performance in production, track input and output metric alignment, and provide clear visibility into how platform capabilities contribute to customer-facing outcomes.
Partner with cross-functional stakeholders and leadership to align on priorities and trade-offs.
Drive adoption of platform capabilities across teams by ensuring solutions are intuitive, reliable, and measurably better than existing workflows.