NLP PEOPLE
Senior Associate Machine Learning Engineer
NLP PEOPLE, 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. And when we began to rise, one thing that really set us apart was our culture. A culture which was driven by our value of putting our people first. And ever since, the happiness, development, and contribution of every Workmate is central to who we are. Our Workmates believe a healthy employee-centric, collaborative culture is the essential mix of ingredients 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. You can feel the energy and the passion, it’s what makes us unique. 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 Team
Do you dig data? Scads and scads of data. We guess you probably do since you’re looking at a Machine Learning job ad. Payroll data … super dry stuff, huh? Well, truth is, only a subset of the population uses online shopping, or orders food deliveries, or binges TV series. But everyone, EVERYONE!, who gets paid has payroll data. More of it every month, every day, every hour. Payroll has more or less done the same thing since it was the first ever automated business application built in the 1950s. But we believe that using modern Machine Learning techniques, we can transform the way that Payroll is processed. So if you like working with huge volumes of vital data and you are interested in a goal of making people’s lives better by ensuring they get paid correctly, accurately, swiftly for the work they do, we’d love to talk to you!About the Role
As 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 a variety of ML models to create and enhance next generation AI experience for various user personas of Workday Payroll products. You will work closely with product managers and developers to deliver AI solutions that provide users value and efficiency. Your work ensures that users have the best experience and increased productivity from predictive analytics, recommendations and assistant features.Responsibilities
Be part of a team of software developers and machine learning engineers that develops responsible AI features for Payroll products.Learn about enterprise HR/Payroll application data and processes.Own data exploration and transformation, feature engineering, design-train-enhance ML models/frameworks that deliver anomaly detection, prediction, recommendation, document intelligence and AI agent features for Payroll product.Work on end to end ML Data engineering pipeline, Model development, 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 and a forward-looking company.About You
Basic Qualifications:
2+ yrs experience as part of a data engineering, machine learning software development team or relevant work in a graduate academic program.Proficiency in Python, supporting numeric libraries and data engineering tools e.g. Pandas and PySpark etc.Experience in machine learning frameworks & toolkits such as Tensorflow, Pytorch, Sklearn etc.Familiarity of different LLMs and their strength/weakness to solve diverse problems.Experience building applied ML/AI products, including taking a product through design, implementation, and to 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 used in AI/ML capabilities development, deployment and monitoring.Self motivated with a strong sense of ownership, urgency and resiliency.Strong communication and interpersonal skills.Workday Pay Transparency Statement
The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate’s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things.Our Approach to Flexible Work
With 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, prospects, and partners (depending on role). This means you’ll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together.Equal Opportunity Statement
Workday is proud to be an equal opportunity workplace. Individuals seeking employment at Workday are considered without regards to age, ancestry, color, gender (including pregnancy, childbirth, or related medical conditions), gender identity or expression, genetic information, marital status, medical condition, mental or physical disability, national origin, protected family care or medical leave status, race, religion (including beliefs and practices or the absence thereof), sexual orientation, military or veteran status, or any other characteristic protected by federal, state, or local laws.
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Do you dig data? Scads and scads of data. We guess you probably do since you’re looking at a Machine Learning job ad. Payroll data … super dry stuff, huh? Well, truth is, only a subset of the population uses online shopping, or orders food deliveries, or binges TV series. But everyone, EVERYONE!, who gets paid has payroll data. More of it every month, every day, every hour. Payroll has more or less done the same thing since it was the first ever automated business application built in the 1950s. But we believe that using modern Machine Learning techniques, we can transform the way that Payroll is processed. So if you like working with huge volumes of vital data and you are interested in a goal of making people’s lives better by ensuring they get paid correctly, accurately, swiftly for the work they do, we’d love to talk to you!About the Role
As 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 a variety of ML models to create and enhance next generation AI experience for various user personas of Workday Payroll products. You will work closely with product managers and developers to deliver AI solutions that provide users value and efficiency. Your work ensures that users have the best experience and increased productivity from predictive analytics, recommendations and assistant features.Responsibilities
Be part of a team of software developers and machine learning engineers that develops responsible AI features for Payroll products.Learn about enterprise HR/Payroll application data and processes.Own data exploration and transformation, feature engineering, design-train-enhance ML models/frameworks that deliver anomaly detection, prediction, recommendation, document intelligence and AI agent features for Payroll product.Work on end to end ML Data engineering pipeline, Model development, 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 and a forward-looking company.About You
Basic Qualifications:
2+ yrs experience as part of a data engineering, machine learning software development team or relevant work in a graduate academic program.Proficiency in Python, supporting numeric libraries and data engineering tools e.g. Pandas and PySpark etc.Experience in machine learning frameworks & toolkits such as Tensorflow, Pytorch, Sklearn etc.Familiarity of different LLMs and their strength/weakness to solve diverse problems.Experience building applied ML/AI products, including taking a product through design, implementation, and to 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 used in AI/ML capabilities development, deployment and monitoring.Self motivated with a strong sense of ownership, urgency and resiliency.Strong communication and interpersonal skills.Workday Pay Transparency Statement
The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate’s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things.Our Approach to Flexible Work
With 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, prospects, and partners (depending on role). This means you’ll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together.Equal Opportunity Statement
Workday is proud to be an equal opportunity workplace. Individuals seeking employment at Workday are considered without regards to age, ancestry, color, gender (including pregnancy, childbirth, or related medical conditions), gender identity or expression, genetic information, marital status, medical condition, mental or physical disability, national origin, protected family care or medical leave status, race, religion (including beliefs and practices or the absence thereof), sexual orientation, military or veteran status, or any other characteristic protected by federal, state, or local laws.
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