Full Job Description
We are looking for an exceptional Engineering Manager with experience leading teams responsible for building and operating large-scale distributed services. And, wants to use that experience to lead a team responsible for designing, building and running a scale platform designed for machine learning and is critical to the success of ML engineers throughput RAD-G. In this role, you will define objectives for key products in the Machine Learning Platform, own the technical roadmap for a product, be accountable for delivering on results and making our ML customer throughout Apple successful. You will do this by growing and developing a diverse engineering team, coaching engineers to grow and become technical leaders.
- Delivered services with measurable impact on internal or external customers
- Influenced product and technical direction by being a customer advocate
- 10+ years experience building production services in a distributed computing environment
- Deployed mission-critical services with high reliability and available
- Driven projects from inception to production
- An understanding of distributed system concepts (such as transactions and consensus) in practice
- Ability to present and communicate complex technical concepts clearly
- Experience with partnering with other technical stakeholders
- Demonstrated technical leadership through influence and mentoring
- In-depth experience building solutions using public clouds (Azure, AWS, GCP)
- Experience leading teams through building and operating large-scale services
- Comfortable working in earlier stages of product development with ambiguous requirements
- Have experience and in-depth knowledge of open source distributed systems such as Hadoop, Spark, Zookeepr, etcd, Cassandra, Kubernetes
- Have 2+ more years of experience leading teams
- Have a passion to create and try new ideas.
- Accept some travel and long hours on occasion.
- Willing to work on new and diverse technologies as opposed to developing perfection in one area.
- Permanent position, 40 hours/week
- Remote applicants are welcome