Asks for

The ad says“Bachelor’s (Master’s or PhD preferred) degree in engineering, data/computer science, physics, math or equivalent”
The ad says“Bachelor’s (Master’s or PhD preferred) degree in engineering, data/computer science, physics, math or equivalent”
The ad says“Bachelor’s (Master’s or PhD preferred) degree in engineering, data/computer science, physics, math or equivalent”
The ad says“Bachelor’s (Master’s or PhD preferred) degree in engineering, data/computer science, physics, math or equivalent”
The ad says“Bachelor’s (Master’s or PhD preferred) degree in engineering, data/computer science, physics, math or equivalent”
The ad says“Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation”
The ad says“3+ years of full-time professional experience with cloud computing platforms (e.g. AWS, GCP, etc.)”
The ad says“3+ years of full-time professional experience with data engineering and data wrangling using e.g. Pandas and PySpark and other industry tools used to build scalable machine learning systems, such as Kubernetes and Docker”
The ad says“3+ years of full-time hands-on professional experience in developing ETL pipelines and inference services that use large language models (LLMs) and text generation models in production. This includes the full machine learning life cycle - data processing, model fine-tuning, model deployment and model evaluation”
The ad says“3+ years of full-time professional experience with cloud computing platforms (e.g. AWS, GCP, etc.)”
The ad says“3+ years of full-time hands-on professional experience in developing ETL pipelines and inference services that use large language models (LLMs) and text generation models in production. This includes the full machine learning life cycle - data processing, model fine-tuning, model deployment and model evaluation”
The ad says“3+ years of full-time professional experience in building information retrieval systems.”
The ad says“3+ years of full-time professional experience with data engineering and data wrangling using e.g. Pandas and PySpark and other industry tools used to build scalable machine learning systems, such as Kubernetes and Docker”
The ad says“Apply machine learning techniques including LLMs and natural language understanding to analyze large sets of HR and Finance-related text data, and design and launch pioneering cloud-based machine learning architectures”
The ad says“You are a strong technical leader with deep Python expertise and solid machine learning engineering skills, capable of writing beautiful, well-designed code while delivering solutions efficiently. Specifically, you will:”
The ad says“Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms, and natural language processing for information retrieval and/or recommendation system use cases”
The ad says“Apply machine learning techniques including LLMs and natural language understanding to analyze large sets of HR and Finance-related text data, and design and launch pioneering cloud-based machine learning architectures”
The ad says“Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation”
The ad says“3+ years of full-time professional experience with data engineering and data wrangling using e.g. Pandas and PySpark and other industry tools used to build scalable machine learning systems, such as Kubernetes and Docker”
The ad says“3+ years of full-time professional experience with data engineering and data wrangling using e.g. Pandas and PySpark and other industry tools used to build scalable machine learning systems, such as Kubernetes and Docker”
The ad says“You are a strong technical leader with deep Python expertise and solid machine learning engineering skills, capable of writing beautiful, well-designed code while delivering solutions efficiently. Specifically, you will:”
The ad says“3+ years of full-time professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow, and Sklearn”
The ad says“Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation”
The ad says“3+ years of full-time professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow, and Sklearn”
The ad says“Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms, and natural language processing for information retrieval and/or recommendation system use cases”
The ad says“3+ years of full-time professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow, and Sklearn”

Your work days are brighter here.

We’re 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, we’re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you’ll 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. We’re 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 you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. In return, we’ll 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, you’ve found a match in Workday, and we hope to be a match for you too.

About the Team

Do you want to build AI-powered software that impacts millions of people every day? The AI Foundations team, part of Workday’s AI Platform organization, tackles challenging problems at the intersection of machine learning, agentic reasoning, and enterprise-scale systems. Our work delivers critical AI platform capabilities and differentiated, deep-value agent applications.

About the Role

As a Machine Learning Engineer on the AI Platform team, you will develop tailored user experiences using advanced Agentic AI, LLMs and RAG. You will collaborate with other engineers to deliver ML solutions across Workday’s product ecosystem and use current software and data engineering stacks to enable training, deployment, and lifecycle management of a variety of ML models; supervised and unsupervised. Additionally, you will develop and deploy new APIs/services using Docker/Kubernetes at scale and leverage Workday’s vast computing resources on rich datasets to deliver transformative value to our customers. Sound like your kind of challenge?

About You

You are a strong technical leader with deep Python expertise and solid machine learning engineering skills, capable of writing beautiful, well-designed code while delivering solutions efficiently. Specifically, you will:

Own exploration, design and implementation of features for our sophisticated ML platforms, pipelines and services.
Be responsible for evaluation, scalability and observability of these features.
Apply machine learning techniques including LLMs and natural language understanding to analyze large sets of HR and Finance-related text data, and design and launch pioneering cloud-based machine learning architectures
Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation

Basic Qualifications:

Bachelor’s (Master’s or PhD preferred) degree in engineering, data/computer science, physics, math or equivalent
3+ yrs full-time professional experience as a member of a data science, machine learning engineering, or other relevant software development team building machine learning products from the ground up at scale. This includes taking products through applied research, design, implementation, evaluation, and production.
3+ years of full-time hands-on professional experience in developing ETL pipelines and inference services that use large language models (LLMs) and text generation models in production. This includes the full machine learning life cycle - data processing, model fine-tuning, model deployment and model evaluation
3+ years of full-time professional experience with Python and supporting libraries in production
3+ years of full-time professional experience with data engineering and data wrangling using e.g. Pandas and PySpark and other industry tools used to build scalable machine learning systems, such as Kubernetes and Docker
3+ years of full-time professional experience with cloud computing platforms (e.g. AWS, GCP, etc.)
3+ years of being able to communicate clearly and effectively in a cross-functional setting with product managers, app teams, and leadership

Other Qualifications:

3+ years of full-time professional experience in building information retrieval systems.
3+ years of full-time professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow, and Sklearn
Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms, and natural language processing for information retrieval and/or recommendation system use cases

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. For more information regarding Workday’s comprehensive benefits, please click here.

Primary Location: USA.CA.Pleasanton

Primary Location Base Pay Range: $160,000 USD - $240,000 USD

Additional US Location(s) Base Pay Range: $136,200 USD - $240,000 USD

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. 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.

Workday is committed to providing reasonable accommodations for qualified individuals during our application process, in order to perform one or more essential functions of their job, as well as regarding the use of AI tools for employment decision-making to any degree. Please see below for more details including how to request an accommodation as a qualified veteran, due to a disability or for religious reasons, or as otherwise provided under applicable law.

Workday prohibits taking adverse action against any candidate or employee for reporting a possible violation of this policy, requesting one or more work accommodations, exercising a privacy right, or cooperating in an investigation in accordance with applicable law. Any employee who retaliates against a candidate or employee for doing so may be subject to disciplinary action, up to and including termination of employment, to the fullest extent allowable under applicable law.

If you require a reasonable accommodation, you may email accommodations@workday.com, as far in advance as possible.

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.