machine learning engineer, Principal, Starbucks Technology - Seattle,

  • Starbucks
  • Seattle, WA, USA
  • Mar 26, 2020
Full time Biotech Science

Job Description

Description:

Job Summary and Mission

This position contributes to Starbucks success by driving advancements to Enterprise Data & Analytics Platform and will support the definition, build out, evangelism and deployment of foundational AI capabilities that are critical to democratizing Machine Learning and AI driven applications across the organization.

Models and acts in accordance with Starbucks guiding principles.

Summary of Key Responsibilities

Responsibilities and essential job functions include but are not limited to the following\:

  • Forge partnerships with the Analytics teams across Starbucks as well as Technology teams to clearly understand business domains (domain proficiency) as well as demonstrate technical depth to gain trust and partnership

  • Perform Industry Research, develop working prototypes and prove the concepts for key trends in development, deployment and operating Machine Learning / Deep Learning models in production

  • Translate strategic analytics requirements into Analytics tools and infrastructure

  • Engineering production grade platform solutions that are secure, scalable and supportable.

  • Evangelize platform capabilties through strategic partnership, rapid prototyping of usecases.

  • Identify, document and promote best practices across the organization


Qualification:

Summary of Experience\: Software Engineering\:•Experience in one of the public cloud platforms such as Azure/AWS/GCP and designing Cloud Native solutions.•Demonstrated experience in distributed computing systems such as Apache Spark or similar (1+ years)•Demonstrated experience and expertise in programming using languages such as Python or Scala or equivalent. (5 years)•Demonstrated experience in using state of the art DevOps techniques in the context of Machine Learning powered applications.(1 year)•Experience in Containerization of applications, Kubernetes and Microservices .(1 year)•Exposure to Site Reliability Engineering best practices(1 year)•Demonstrated experience in building, deploying and operating ATLEAST ONE ML powered application at Scale in production.(1 year)Applied Machine Learning\:•Appreciation of Math concepts such as linear algebra, Bayesian statistics, group theory desirable.•Experience or exposure to application of Machine Learning algorithms ( classification, regression, or ranking problems) to real world applications.•Experience or exposure to application of deep learning/neural networks and machine learning frameworks like Tensorflow or Keras or equivalent to real world problems.General\:•Proven track record of being part of successful agile teams, collaborating with Engineers, Data Engineers, Data Scientists and business stake holders and delivering engineering outcome.•Overall experience (5+ years)•Experience working in Retail domain desirable.Basic Qualifications\:•MS / BS with concentration in quantitative discipline - Stats, Math, Comp Sci, Engineering, Econ, Quantitative Social Science or similar discipline .Required Knowledge, Skills, and Abilities•Technical proficiency to deal with complex problems that have now evolved from ideation and consulting•Ability to apply knowledge of multidisciplinary business principles and practices to achieve successful outcomes in cross-functional projects and activities•Security proficiency to design and implement complex compliance controls•Ability to take Input from industry trends to help shape platform needs by demonstrating application and platform expertise •Ability to apply knowledge of multidisciplinary business principles and practices to achieve successful outcomes in cross-functional projects and activities•Technical skillsPractical working skills in leading Machine Learning / Deep Learning Frameworks like TensorFlow, KerasPractical skills in querying and processing Big Data using Apache Spark, SQL.Expert Programming skills in Python or Scale or equivalentExpert DevOps skills using platform like Jenkins, Azure Dev Ops or equivalentExpert skills in Kubernetes , Containers and Micro Services deployment Starbucks and its brands are an equal opportunity employer of all qualified individuals. We are committed to creating a diverse and welcoming workplace that includes partners with diverse backgrounds and experiences. We believe that enables us to better meet our mission and values while serving customers throughout our global communities. People of color, women, LGBTQIA+, veterans and persons with disabilities are encouraged to apply. Qualified applicants with criminal histories will be considered for employment in a manner consistent with all federal state and local ordinances. Starbucks Corporation is committed to offering reasonable accommodations to job applicants with disabilities. If you need assistance or an accommodation due to a disability, please contact us at or via email at