Job description
Day to day responsibilities include working with multiple product and Software QE and ML Evaluation teams to understand their requirements for evaluation of ML models and translating them into a roadmap. You will also work with the platform development team and key cross functional partners to prioritize and deliver this roadmap. In addition, you will partner with teams across Siri to drive adoption of the platform. Communication and presentation skills will be key to success in this role. In particular, you will: Communicate: Effectively communicate technical concepts to engineering partners, and executive team. Develop compelling presentations and documentation to showcase the capabilities and benefits of the ML evaluation platforms. Provide insights and recommendations based on evaluation findings. Engage with potential partners to understand their requirements and tailor presentations accordingly. Act as a liaison between technical teams and external partners, addressing queries and concerns. Build and maintain strong relationships with internal and external stakeholders. Platform Advocacy: Act as a spokesperson for the ML evaluation platforms, advocating its features, benefits, and potential applications. Develop internal marketing collateral and participate in meetings/internal events to promote the ML evaluation platforms. Work closely with engineering partner teams to support the platform's integration into new partnerships. Problem solving: Collaborate with machine learning engineers and data scientists to analyze and interpret results from ML experiments. Proactively identify issues/gaps and design and implement evaluation frameworks for assessing the performance and feasibility of ML technologies. Plan: Collaborate with engineering, data science, and product teams to define project scope and objectives. Create and manage project timelines with clear dependencies, critical path and systematic methodology to communicate status. Manage risks and mitigations, and re- plan as events warrant. Drive alignment across the organization and between teams Coordinate: Coordinate discussions with cross-functional teams involved in the evaluation of ML technologies. Collaborate with engineering, data science, and product teams to define project scope and objectives. Develop and manage project plans, ensuring achievements and deadlines are met. Implement: Drive on time delivery and deployment, identifying development and feasibility needs, establishing achievements for checkpoints and status updates
Address
Cupertino, CA
