29 days old

Machine Learning Engineer - Splunk

San Jose, California

Join us as we pursue our disruptive new vision to make machine data accessible, usable and valuable to everyone. We are a company filled with people who are passionate about our product and seek to deliver the best experience for our customers. At Splunk, we’re committed to our work, customers, having fun and most importantly to each other’s success. Learn more about Splunk careers and how you can become a part of our journey!
Role 
Splunk’s Machine Learning team is looking for an experienced machine learning engineer who can design, build, test, and support our batch and streaming machine learning and data solutions for on-premise and cloud platforms. The ideal candidate will have significant experience in designing, developing and deploying machine learning algorithms at scale. You have a customer-focused approach and will set the provide technical direction to the team.

Responsibilities

Splunk engineers are passionate about continuously improving both what we deliver, and how we deliver our product to customers. As the machine learning engineer, you will

  • Design, develop, and productionize data science and engineering capabilities in Splunk’s machine learning infrastructure.
  • Implement, test, and benchmark key software improvements and performance optimizations
  • Work with team members on implementing algorithms efficiently
  • Present technical ideas and solutions to the team including software engineers, architects, and business leaders.
  • Be a high-performing team player who enjoys collaborating with, learning from, mentoring, and teaching other team members to create a positive work environment.

Requirements

Requirements 

  • 5+ years of experience deploying enterprise production systems in Python, Java, Scala or C++.
  • Strong knowledge of computer science fundamentals such as algorithms and data structures.
  • Software development experience in cloud computing or distributed systems
  • Experience with unit testing, and performance benchmarking and tuning.
  • Knowledge of machine learning frameworks such as scikit-learn, SparkML, or Tensorflow, and tools such as notebooks (Jupyter, Zepellin).
  • Experience with container and orchestration technologies, such as Docker and Kubernetes.
  • Bachelor in Computer Science or related fields.

Categories

Posted: 2019-07-19 Expires: 2019-09-17

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Machine Learning Engineer - Splunk

Splunk
San Jose, California

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