Software Engineer - Data Pipelines for Machine Learning

Zurich, Zurich, Switzerland
Hardware

Summary

Posted: 20. Dec 2018
Role Number: 200023148
Our team is focused on real-time computer vision and image processing, combining modern machine learning approaches with geometric knowledge from Computer Vision. In the context of machine learning we need to collect large amounts of data, push it reliably through data processing pipelines, let large clouds crunch on it, continuously verify and report the accuracy of the resulting algorithms, and finally transfer trained models to products. We are working on the cutting edge of academic research while creating shipping features, such as portrait mode, ARKit and Animoji. We are looking for a talented Software Engineer to shape the future of our data pipelines. You will be working in a diverse, fast moving team based in Zürich and will interact regularly with teams based in Cupertino, USA.

Key Qualifications

  • High-level understanding as well as hand-on experience in implementing data pipelines
  • Proficient in scripting languages such as Python, Bash, Groovy, Ruby
  • Experience with database, message queueing, and data streaming solutions (for instance: PostgreSQL, Apache Kafka, AWS Kinesis, RabbitMQ, Redis, Apache Spark, or similar tools)
  • Experience with DevOps and application monitoring tools is a plus (for instance: Docker, Chef, Puppet, Ansible, Salt, Splunk, Elastic/ELK Stack, Sentry, Datadog, or similar tools)
  • Experience in (regression) testing data pipelines
  • Knowledge of Mac and Linux environments is a plus
  • Knowledge of Machine Learning and Computer Vision is a plus
  • Fluency in English is required

Description

You will be working on data pipelines to support the development of the next generation video and image analysis projects in our computer vision research. Our work is focused on real time performance and finds its way into the whole range of future apple products. Your contribution will ensure that Apple delivers these products with the highest quality.

Education & Experience

Bachelor / Master Computer Science or equivalent work experience

Additional Requirements