Staff Machine Learning Infrastructure Engineer

Company: Intuit
Location: Mountain View
Posted on: April 9, 2021

Job Description:

OverviewIntuit AI is paving the way in Machine Learning and Artificial Intelligence for all facets of the Intuit product suite, allowing Intuit to power prosperity for everyone. Intuit AI Engineering is a dynamic and innovative group whose mission is to enhance overall engineering capabilities for the purpose of improving efficiency, productivity, and impact of AI practitioners. In this team, you'll be tasked with owning and delivering cutting edge platforms, frameworks, and services that power AI at Intuit.-Machine Learning Infrastructure Engineers work at the intersection of software and systems engineering to design and build large scale consumer experiences which are reliable, operable, secure, highly available, disaster-ready, and performant. Join a world-class operations team and utilize your programming and operations talents to apply the latest patterns in continuous delivery, cloud operations, containerization, and serverless technology and help us build the next generation AI/ML platform and delight millions of customers.What you'll bring

• BS, MS, in Computer Science or a related field, or equivalent practical experience.
• 3+ years of cloud experience, working collaboratively with development teams, assisting with build and production support, writing deployment automation, setting up CI/CD pipelines, etc.
• Knowledge of data query and data processing tools (i.e. SQL)
• 2+ years of solid Configuration Management experience: (For example Chef, Puppet, Salt, Ansible, Cfengine, etc
• Knowledge of agile project methodologies. Experience with writing user stories in Jira, grooming project backlogs, planning sprints, and working with Scrum or Kanban
• Solid understanding of networking including TCP/IP stack, basic switching/routing concepts, and load-balancing
• Experience with-CI/CD-tools (Jenkins/Jenkins2, Spinnaker, CodePipeline, TeamCity, Bamboo, etc)
• Experience with big data stores and NoSQL databases (EMR (spark, hive, hadoop) - preferred, Vertica - preferred, Cassandra, Redshift, Kinesis, or AWS Elasticsearch)
• Experience with software container technology (e.g., Kubernetes, Docker)Additional Qualifications
  • Team player possessing strong analytical, problem-solving and communication skills
  • Demonstrated ability to work with global teams across time zones
  • Ability to work effectively in a fast-paced, complex technical environment
  • High adaptability and flexibility
  • Experience driving for results across cross-functional teams while maintaining effective working relationships
  • Self-starter attitude and the ability to make decisions independentlyHow you will leadIn this role, you'll be part of a vibrant team of data scientists, product developers, and machine learning engineers.- You'll be expected to help architect, code, optimize, and deploy machine learning models at scale using the latest industry tools and techniques.- You will be responsible for defining and maintaining the day to day as well as the future operations and reliability for a variety of use-cases. You will also help automate, deliver, monitor, and improve machine learning solutions while ensuring data and models are secure.--

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