Workday
Senior Associate Machine Learning Engineer
Workday, Atlanta, Georgia, United States, 30383
Your work days are brighter here.
At Workday, it all began with a conversation over breakfast. When our founders met at a sunny California diner, they came up with an idea to revolutionize the enterprise software market. Our culture, driven by our value of putting our people first, has been central to who we are. Our Workmates believe a healthy employee-centric, collaborative culture is essential for success in business. That’s why we look after our people, communities, and the planet while still being profitable. Feel encouraged to shine, however that manifests: you don’t need to hide who you are. Inspired to make a brighter work day for all and transform with us to the next stage of our growth journey? Bring your brightest version of you and have a brighter work day here.
About the TeamDo you dig data? Scads and scads of data. Payroll data is vital and impacts everyone who gets paid. We believe that using modern Machine Learning techniques, we can transform the way that Payroll is processed. If you like working with huge volumes of vital data and are interested in making people’s lives better by ensuring they get paid correctly and swiftly, we’d love to talk to you!
About the RoleAs a Machine Learning Engineer, you will help develop data-driven, automated, comprehensive application solutions using the latest AI and Data Engineering technologies. Your work enables deployment and lifecycle management of various ML models to create and enhance the next generation AI experience for Workday Payroll products. You will work closely with product managers and developers to deliver AI solutions that provide users value and efficiency.
In this role, you would:
Be part of a team developing responsible AI features for Payroll products.
Learn about enterprise HR/Payroll application data and processes.
Own data exploration and transformation, feature engineering, and design-train-enhance ML models/frameworks.
Work on the end-to-end ML Data engineering pipeline, Model development, and deployment in production at scale.
Develop, maintain, and enhance ML solutions that are highly usable, scalable, and secured.
Grow your career in a great place to work.
About YouBasic Qualifications:
2+ years of experience in a data engineering or machine learning software development team or relevant graduate academic program.
Proficiency in Python and data engineering tools (e.g., Pandas, PySpark).
Experience in machine learning frameworks & toolkits (Tensorflow, Pytorch, Sklearn).
Familiarity with different LLMs and their strengths/weaknesses.
Experience building applied ML/AI products through design, implementation, and production.
Other Qualifications:
B.S. in relevant fields (Computer Science, Machine Learning, Engineering); graduate degree is a plus.
Hands-on experience with the RAG approach to leverage LLMs is a plus.
Experience with AWS data engineering and computing platforms.
Self-motivated with a strong sense of ownership, urgency, and resiliency.
Strong communication and interpersonal skills.
Workday Pay Transparency StatementThe annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. This role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Each candidate’s compensation offer will be based on multiple factors including geography, experience, skills, job duties, and business need.
Primary Location: USA.GA.AtlantaPrimary Location Base Pay Range: $122,700 USD - $184,100 USDAdditional US Location(s) Base Pay Range: $116,600 USD - $212,800 USD
Our Approach to Flexible WorkWith Flex Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers.
Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records. Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.
#J-18808-Ljbffr
At Workday, it all began with a conversation over breakfast. When our founders met at a sunny California diner, they came up with an idea to revolutionize the enterprise software market. Our culture, driven by our value of putting our people first, has been central to who we are. Our Workmates believe a healthy employee-centric, collaborative culture is essential for success in business. That’s why we look after our people, communities, and the planet while still being profitable. Feel encouraged to shine, however that manifests: you don’t need to hide who you are. Inspired to make a brighter work day for all and transform with us to the next stage of our growth journey? Bring your brightest version of you and have a brighter work day here.
About the TeamDo you dig data? Scads and scads of data. Payroll data is vital and impacts everyone who gets paid. We believe that using modern Machine Learning techniques, we can transform the way that Payroll is processed. If you like working with huge volumes of vital data and are interested in making people’s lives better by ensuring they get paid correctly and swiftly, we’d love to talk to you!
About the RoleAs a Machine Learning Engineer, you will help develop data-driven, automated, comprehensive application solutions using the latest AI and Data Engineering technologies. Your work enables deployment and lifecycle management of various ML models to create and enhance the next generation AI experience for Workday Payroll products. You will work closely with product managers and developers to deliver AI solutions that provide users value and efficiency.
In this role, you would:
Be part of a team developing responsible AI features for Payroll products.
Learn about enterprise HR/Payroll application data and processes.
Own data exploration and transformation, feature engineering, and design-train-enhance ML models/frameworks.
Work on the end-to-end ML Data engineering pipeline, Model development, and deployment in production at scale.
Develop, maintain, and enhance ML solutions that are highly usable, scalable, and secured.
Grow your career in a great place to work.
About YouBasic Qualifications:
2+ years of experience in a data engineering or machine learning software development team or relevant graduate academic program.
Proficiency in Python and data engineering tools (e.g., Pandas, PySpark).
Experience in machine learning frameworks & toolkits (Tensorflow, Pytorch, Sklearn).
Familiarity with different LLMs and their strengths/weaknesses.
Experience building applied ML/AI products through design, implementation, and production.
Other Qualifications:
B.S. in relevant fields (Computer Science, Machine Learning, Engineering); graduate degree is a plus.
Hands-on experience with the RAG approach to leverage LLMs is a plus.
Experience with AWS data engineering and computing platforms.
Self-motivated with a strong sense of ownership, urgency, and resiliency.
Strong communication and interpersonal skills.
Workday Pay Transparency StatementThe annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. This role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Each candidate’s compensation offer will be based on multiple factors including geography, experience, skills, job duties, and business need.
Primary Location: USA.GA.AtlantaPrimary Location Base Pay Range: $122,700 USD - $184,100 USDAdditional US Location(s) Base Pay Range: $116,600 USD - $212,800 USD
Our Approach to Flexible WorkWith Flex Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers.
Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records. Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.
#J-18808-Ljbffr