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!
Splunk’s Machine Learning team is looking for a Principal Machine Learning Engineer who can design, build, test, and support our batch and streaming machine learning services at scale. These services will be used in solutions for both on-premise and cloud deployments, and they form a core part of our current and next-generation product offerings.
Splunk engineers are passionate about continuously improving both what we deliver, and how we deliver our product to customers. As a Principal Machine Learning Engineer, you will:
- Drive the system architecture and design decisions for Splunk’s machine learning infrastructure, for both cloud and on premise environments, and for both batch and stream based processing.
- Design, develop, determine test strategy, test, and maintain key software improvements related to machine learning capabilities at Splunk.
- Work in a team with product managers and data scientists, as the software engineering technical leader, to develop novel solutions for our most difficult data based challenges.
- Be a team player who enjoys collaborating with, learning from, mentoring, and teaching other team members to create a positive work environment.
- 8+ years of commercial or open source product development experience, preferably in large scale cloud computing and/or distributed systems environments.
- 4+ years of professional experience developing solutions using data pipelines, popular machine learning frameworks (scikit-learn, SparkML, or Tensorflow), and notebook based experimentation tools (Jupyter, Zepellin).
- 8+ years of programming in large scale production systems, in languages such as Python, Java, Scala or C++.
- A strong interest and preferably a strong background in mathematics, such that you are able to collaborate effectively in design discussions with machine learning researchers and data scientists.
- Bachelors in Computer Science or related fields.
Nice to have:
- Expertise in developing software with containers and container orchestration technologies, such as Docker and Kubernetes.
- Expertise in developing software on a public cloud platform (e.g. AWS, GCP, MS Azure etc.)
- Expertise in developing software with stream processing technology (e.g. Flink, Kafka, etc.)
We value diversity at our company. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or any other applicable legally protected characteristics in the location in which the candidate is applying.
For job positions in San Francisco, CA, and other locations where required, we will consider for employment qualified applicants with arrest and conviction records