Senior Software R&D Engineer - Big Data Machine Learning Platform

Hyderabad, Telangana, India
Software and Services


Weekly Hours: 40
Role Number:200114066
The people here at Apple don’t just build products — they build the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it. Imagine what you could do here. At Apple, we work every day to create products that enrich people’s lives. Our Apple Online Store Engineering technology and services power the Apple Online Store and Retail systems. Our platforms are highly performant and deployed at scale. The Apple Online Store Machine Learning Platform is looking for a self-driven engineer who will help deliver data solutions to key technical problems. As part of a small team, you will own significant responsibility for critical products which help customers make the best use of their data and optimize their performance. You will build a deep understanding of the data sets that are the foundation of the business and apply statistical / machine learning models to solve complex problems demonstrating your strong data science skills. You will build scalable data pipelines and reliable services. You will collaborate across other engineering teams, data scientists, product managers and business operations to not only build the features, but validate, measure and experiment at scale. As a member of the Machine Learning Platform team, you will have significant responsibility and influence in shaping its future direction. This role is inherently cross functional and the ideal candidate will work across disciplines. We are looking for someone with a love for data and ability to iterate quickly on all stages of a data pipeline. This position involves developing large scale data pipelines and analytical solutions using Big Data technologies. Successful candidates will have strong data science, engineering and interpersonal skills, as well as a belief that data driven processes lead to phenomenal products. You will need to have a passion for quality and an ability to understand complex systems.

Key Qualifications

  • Industry experience in crafting, implementing and delivering complex, scalable and resilient data pipelines and services.
  • You need to have a deep understanding of distributed systems and data processing technologies (Hadoop, MapReduce, Oozie, Flume, Spark batch / streaming / SQL, Cassandra, Kafka, Solr, Impala).
  • Strong programming skills with proficiency in Java, Scala, Python and SQL.
  • Proven understanding of machine learning techniques and algorithms, such as Naive Bayes, SVM, k-NN, Decision Trees, Random Forests, etc.
  • Experience with common data science toolkits, such as R, Python scikit-learn, NumPy, Weka, MatLab, etc. Excellence in few of these is a necessity.
  • Strong industry experience in machine learning algorithms and efficient ways of their productization at scale.
  • Good team worker who can collaborate well with multi-functional teams
  • Ability to efficiently handle and implement quick- turnaround, tactical projects as a team player
  • Commitment to resolve problems expeditiously at all times
  • Strong written, verbal, and presentation skills
  • Ability to apply creative, out of the box thinking
  • Strong problem-solving and analytical abilities
  • Ability to rapidly learn new technologies


• Strong analytical skills. • Experience with integrating model training, inference, and decisioning in batch and real-time data pipelines. • Clear and effective communicator with a collaborative mindset. • Experience with large scale data warehousing, mining or analytic systems. • Ability to work with analysts to gather requirements and translate them into data engineering tasks. • The ability to independently learn new technologies.

Education & Experience

Bachelors/Masters in Computer Science or similar discipline. 5+ yrs of professional experience.

Additional Requirements