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Uber is on the lookout for an outstanding leader to drive innovation for Uber's Machine Learning Platform (Michelangelo). This role involves building and managing robust distributed systems and tackling infrastructure challenges to empower Uber’s product engineering and data science teams with the latest technologies in large-scale Artificial Intelligence. The Michelangelo team works on building end-to-end ML systems and up-leveling ML quality at Uber. You will be part of a team of strong software and systems engineers, performing in a fast-paced environment.
Job Responsibility:
Manage a team with a mission to bring up level ML and AI capabilities for all use cases at Uber
Drive the technical alignment internally and with partner teams
Own roadmap execution and delivery of projects with high quality
Contribute to the engineering culture and uphold the processes that will shape the team
Grow, mentor, and develop a team of the backend, ML, and infra engineers
Lean on technical experience to facilitate technical decision-making and improve the team’s engineering craft
Recruit high-quality engineering talent for the team
Requirements:
Experience as a software engineering leader and manager who has built and managed world-class technical teams for at least 6+ years
Proven ability to work with and achieve results as part of a multi-location team
Proven track record of working with large-scale distributed systems (multi-tier architectures, application security, monitoring, and storage systems)
Experience leading engineering teams in parallel execution against high-stakes business goals and extensive engineering priorities
Experience partnering across functions and organizational boundaries to effectively advocate for team, business, and company priorities
A strong ability to architect and design robust, high-scale systems and to challenge engineers to think bigger and more generically in developing their solutions
Nice to have:
Scalable ML Infra Knowledge
Experience in building and managing distributed systems and high-throughput services
Systematic problem-solving approach and knowledge of algorithms, data structures, and complexity analysis
Experienced production user of Deep Learning frameworks such as Apache Spark, XGBoost, Ray, Tensorflow, PyTorch, Keras, Polar, Dask, CUDA, Rocm etc.
Experience in high-performance computing, networking, storage, database, cache or compute