Responsibilities
Develop and implement Measurement Methodologies and Evaluation Frameworks. Assess the performance, accuracy and groundedness of AI Agents, including the automated generation of synthetic training and evaluation data.
Work with various teams including software developers, data engineers and product managers, to define the requirements and implement Gen-AI models and solutions to drive innovation.
Translate complex technical concepts and investigative findings into clear, actionable insights for both technical and non-technical stakeholders.
Lead the design, development and deployment of Generative AI Agents for conversational driving-related experiences and scaling the ingestion, annotation and utilization of user generated contect and geospatial data feeds.
Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of work experience with a PhD degree.
Preferred qualifications:
Master's degree or PhD in Data Science, Computer Science or a related quantitative field.
7 years of experience as a data scientist applying advanced statistical and machine learning methods on real-world problems.
Experience in Generative AI, defining, building and evaluating AI-agents and leveraging foundational language models for introducing advanced new capabilities within existing products and systems.
Experience with relevant libraries and frameworks (e.g., TensorFlow, LangChain, PyTorch, etc.).
Experienced in building and managing large-scale data processing pipelines (e.g., BigQuery).
Experience in Cloud Computing, Machine Learning Operations and in Google Cloud Platform (GCP)/Vertex-AI.
