Apple’s Applied Machine Learning team has built systems for a number of large-scale data science applications. We work on many high-impact projects that serve various Apple lines of business. We use the latest in open source technology and as committers on some of these projects, we are pushing the envelope. Working with multiple lines of business, we manage many streams of Apple-scale data. We bring it all together and extract the value. We do all this with an exceptional group of software engineers, data scientists, dev-ops engineers and managers.
- Have a strong interest in distributed computing, e.g., NoSQL, Cassandra and Hadoop
- Experience with Hadoop based technologies - Hive, Spark, admin management
- Have a passion for automation by creating tools using Python, Java or other JVM languages
- Knowledge of Unix/Linux based operating system, shell scripting
- Excellent problem solving, critical thinking, and communication skills
- The candidate should be adapt at prioritizing multiple issues in a high pressure environment
- Should be able to understand complex architectures and be comfortable working with multiple teams
- Ability to conduct performance analysis and troubleshoot large scale distributed systems
- Should be highly proactive with a keen focus on improving uptime availability of our mission-critical services
- Comfortable working in a fast paced environment while continuously evaluating emerging technologies
- Proficient in unix, command-line tools, and general system debugging
- The position requires solid knowledge of secure coding practices and experience with the open source technologies.
The Senior Infrastructure Engineer in the Applied Machine Learning Team is mainly responsible for managing large scale distributed systems. This position will also help in developing tools necessary to manage large scale mission critical applications.
BS in computer science with 7-10 years or MS plus 5-7 years experience or related experience.