Machine Learning Engineer Evisort

Your work days are brighter here.

Were obsessed with making hard work pay off for our people our customers and the world around us. As a Fortune 500 company and a leading AI platform for managing people money and agents were shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join youll feel it. Not just in the products we build but in how we show up for each other. Our culture is rooted in integrity empathy and shared enthusiasm. Were in this together tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether youre building smarter solutions supporting customers or creating a space where everyone belongs youll do meaningful work with Workmates whove got your return well give you the trust to take risks the tools to grow the skills to develop and the support of a company invested in you for the long haul. So if you want to inspire a brighter work day for everyone including yourself youve found a match in Workday and we hope to be a match for you too.

About the Team

About the Role

As a Machine Learning Engineer you will help develop tailored user experiences using advanced LLMs Knowledge Graphs personalization and predictive analysis. You will collaborate with other engineers to deliver ML solutions across Workdays product ecosystem and utilize software and data engineering stacks to enable training deployment and lifecycle management of various ML models. You will develop and deploy new products at scale and leverage Workdays vast computing resources on rich datasets to deliver transformative value to our customers.

In addition to contributing to feature and service development you must have an approach of continuous improvement passion for quality scale and security. You must be curious and prepared to question or challenge choices and practices where they dont make sense to you or could be improved. You also should have a product approach and strong intuition around how ML can drive a better customer experience. Lastly a strong sense of ownership and teamwork are essential to succeed in this role.

About You

Basic Qualifications

MLE

• 5 years experience as a member of a data science machine learning engineering or other relevant software development team building applied machine learning products at scale including taking products through applied research design implementation production and production-based evaluation

• 2 years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch TensorFlow

• 2 years of professional experience in building services to host machine learning models in production at scale

• 2 years of demonstrated experience working with large language models (LLMs) text generation models and/or graph neural network models for real-world use cases

• 2 years of proven experience with cloud computing platforms (e.g. AWS GCP etc.)

• Bachelors (Masters or PhD preferred) degree in engineering computer science physics math or equivalent

Sr. MLE

• 6 years experience as a member of a data science machine learning engineering or other relevant software development team building applied machine learning products at scale including taking products through applied research design implementation production and production-based evaluation

• 3 years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch TensorFlow

• 3 years of professional experience in building services to host machine learning models in production at scale

• 3 years of demonstrated experience working with large language models (LLMs) text generation models and/or graph neural network models for real-world use cases

• 3 years of proven experience with cloud computing platforms (e.g. AWS GCP etc.)

• Bachelors (Masters or PhD preferred) degree in engineering computer science physics math or equivalent

Other Qualifications:

• Stay up to date with advancements in AI LLMs RAG autonomous agents and orchestration frameworks to drive innovation

• Deep understanding of statistical analysis unsupervised and supervised machine learning algorithms and natural language processing for information retrieval and/or recommendation system use cases

• Professional experience in independently solving ambiguous open-ended problems and technically leading teams

• Excellent interpersonal and communication skills with the ability to build strong relationships across teams and stakeholders

• Proven track record of successfully leading mentoring and/or managing ML Engineering teams taking ownership of development lifecycle and sprint planning; fostering a culture of collaboration transparency innovation and continuous improvement.

Workday Pay Transparency Statement

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 candidates compensation offer will be based on multiple factors including but not limited to geography experience skills job duties and business need among other things. For more information regarding Workdays comprehensive benefits please click here.

Our Approach to Flexible Work

With Flex Work were 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 youll 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. Those in our remote home office roles also have the opportunity to come together in our offices for important moments that matter.

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.

At Workday we are committed to providing an accessible and inclusive hiring experience where all candidates can fully demonstrate their skills. If you require assistance or an accommodation at any point please email .

Are you being referred to one of our roles If so ask your connection at Workday about our Employee Referral process!

At Workday we value our candidates privacy and data security. Workday will never ask candidates to apply to jobs through websites that are not Workday Careers.

Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not.

In addition Workday will never ask candidates to pay a recruiting fee or pay for consulting or coaching services in order to apply for a job at Workday.