ML Engineer

As a Client Engineer, youll design and deliver innovative Machine Learning solutions as part of intelligent products on Databricks and H2O by using core cloud data science tools, Client Ops components, and other big data related technologies. This includes helping lead and craft projects in their initial phases and deliver them with a team. Additionally, youll collaborate closely with a variety of stakeholders across the Workday organization and the Enterprise Data and Architecture teams. What Youll Do Implement models and algorithms on Databricks and H2O Write in Python or other languages to deliver a wide variety of Machine Learning & Data Science solutions Building tools to accelerate feature experimentation and exploration with lineage, data privacy protection and easier model performance debugging. Stay abreast of new tools, packages, and Machine Learning techniques while consistently pushing the limit of what is possible to deliver the best solutions for clients Manage AWS assets including compute, storage, ID management. Collaborate with Product Owners to apply Workdays agile processes and be responsible for the initiation, delivery, and communication of projects for the stakeholder organizations Building Client-as-a-service, with the purpose of taking experiments to production quickly. Share learnings and project findings with the wider Workday Machine Learning Community Willing to work across multiple time zones. What Youll Bring 5+ years of technology industry experience 3 - 4+ years of experience implementing models or machine learning algorithms in production Proficient experience writing SQL, Spark Experience on any of these cloud platforms (AWS, Azure, GCP) Experience developing models and other data science work with Python (preferred) or R (Preferred) Familiarity with Client Ops pipelines or CI/CD implementations (Optional) Quantitative graduate degree (Optional) One or more of the following other languages: Python, R, JavaScript, Go, Scala (Optional) Experience acting as a project manager DataOps Looking for some terraform experience with AWS and Kubernetes. Databricks or Hadoop experience is a must have. 3 years technical implementation of infrastructure design, build and deployment in AWS leveraging Terraform. Implement AWS cloud capabilities including but not limited to EMR,EKS,MSK (Kubernetes is a must) Create and manage CI/CD pipelines using Jenkins or equivalent. Monitor and troubleshoot Databricks/EMR cluster performance issues. Collaborate with development to understand infrastructure needs and provide solutions in a DevOps capacity Automate the delivery of infrastructure services Investigate and resolve technical issue