Senior Machine Learning Engineer

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

What you will do:

• Architect & Build: Design develop and deploy scalable machine learning models and AI systems (ranging from predictive models to Generative AI and LLM-powered agents) that directly impact Workdays core enterprise applications.

• End-to-End Ownership: Take full ownership of the ML lifecycle including data extraction feature engineering model training deployment optimization and continuous monitoring in a high-scale production environment.

• Cross-Functional Collaboration: Partner closely with Data Scientists Software Engineers Product Managers and UX Designers to translate complex business problems into robust AI solutions.

• Drive Technical Excellence: Establish and advocate for engineering best practices robust MLOps processes and highly optimized code.

• Mentorship & Leadership: Guide and mentor junior engineers conduct code and architecture reviews and help shape the technical roadmap for your team.

• Champion Responsible AI: Ensure all models adhere to Workdays strict standards for data privacy security fairness and ethical AI practices.

About You

Basic Qualifications

• Experience: 7 years of industry experience in software engineering with a strong focus on applied machine learning deep learning or NLP.

• Programming Mastery: Expert-level proficiency in Python and strong software engineering fundamentals (data structures algorithms object-oriented design).

• ML Frameworks: Deep hands-on experience with industry-standard machine learning and deep learning libraries (e.g. PyTorch TensorFlow Scikit-learn Hugging Face).

• Production Deployment: Proven track record of taking ML models out of research/notebook environments and deploying them into scalable high-traffic production systems.

• Cloud & Infrastructure: Solid experience with cloud computing platforms (AWS or GCP) and modern infrastructure tools (Docker Kubernetes).

• Education: Bachelors or Masters degree in Computer Science Mathematics Statistics or a related highly quantitative field (or equivalent practical experience).

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 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.

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