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, its 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.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.About the TeamIts fun to work in a company where people truly believe in what theyre doing. At Workday, were committed to bringing passion and customer focus to the business of enterprise applications. We work hard, and were serious about what we do. But we like to have a good time, too. In fact, we run our company with that principle in mind every day: One of our core values is fun. Were working on making machine learning core to Workdays products by building features and capabilities that can be scaled out to hundreds of use cases within Workday. Illuminate: The next generation of Workday AI is unlocking a whole new level of productivity and human potential by accelerating manual tasks, assisting every employee, and ultimately transforming entire business processes. With more than 70 million users under contract generating more than 800 billion transactions a year on our platform, Illuminate leverages the world’s largest and cleanest HR and Finance dataset. The combination of this data—with Illuminate’s ability to understand the context behind it—enables Workday to unlock value in a way no competitor can. Join us as we change the way millions of people work.About the RoleAs 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 Workday’s 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 Workday’s 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. Key Responsibilities:<ul><li>Own exploration, design and execution of advanced ML models, algorithms and frameworks that deliver value to our users.</li><li>Apply machine learning techniques including LLMs, knowledge graphs, deep learning including generative models, natural language understanding, and named entity recognition to analyze large sets of HR and Finance-related text data, and design and launch pioneering cloud based machine learning architectures.</li><li>Own the performance, scalability, metric based deployed evaluation, and ongoing data driven enhancements of your products.</li><li>Keep abreast of the latest advancements in NLP research, techniques, and tools and apply this knowledge onto ML Features.</li><li>Collaborate with a team of innovative engineers to deliver AI-powered agents that integrate deeply into HR and Financial workflows, accelerating intelligent decision making.</li></ul>About YouSenior Machine Learning Engineer:Basic Qualifications:<ul><li>Bachelor’s (Master’s or PhD preferred) degree in engineering, computer science, physics, math or equivalent</li><li>5+ yrs experience as a member of a 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</li><li>5+ years of professional experience with Python and supporting numeric libraries, with experience in shipping production code and models</li><li>3+ years of professional experience in machine learning and deep learning frameworks &amp; toolkits such as Pytorch, TensorFlow, Huggingface</li><li>3+ years of professional experience in building services to host machine learning models in production at scale with cloud computing platforms (e.g. AWS, GCP, etc.)</li><li>3+ years of professional experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases</li></ul>Machine Learning Engineer III:<div>Basic Qualifications</div><div><div><div><div><div><div><div><div><div><ul><li>3+ yrs 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</li><li>1+ years of professional experience in machine learning and deep learning frameworks &amp; toolkits such as Pytorch, TensorFlow</li><li>1+ years of professional experience in building services to host machine learning models in production at scale </li><li>1+ years of demonstrated experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases</li><li>1+ years of proven experience with cloud computing platforms (e.g. AWS, GCP, etc.)</li><li>Bachelor’s (Master’s or PhD preferred) degree in engineering, computer science, physics, math or equivalent</li></ul></div></div></div></div></div></div></div></div></div>Other Qualifications:<ul><li>Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation</li><li>Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms, and natural language processing for information retrieval and/or recommendation system use cases</li><li>Professional experience in independently solving ambiguous, open-ended problems and technically leading teams</li><li>Excellent interpersonal and communication skills, with the ability to build strong relationships across teams and stakeholders</li><li>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</li></ul> 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. 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. For more information regarding Workday’s comprehensive benefits, please <a target="_blank" href="https://workdaybenefits.com/us/welcome-to-workday-benefits/prospective-workmates">click here</a>.Primary Location: USA.CA.Pleasanton  Primary Location Base Pay Range: $198,400 USD - $297,600 USD  Additional US Location(s) Base Pay Range: $167,200 USD - $297,600 USDAdditional Considerations: If performed in Colorado, the pay range for this job is $176,000 - $264,000 USD based on min and max pay range for that role if performed in CO.<div><div><div><div><div><div><div>The application deadline for this role is the same as the posting end date stated as below:  </div></div></div></div></div></div></div>08/20/2025 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 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.Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!