Senior Manager, ML Engineering and Operations
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 TeamWe work hard, play hard while having each other's back. We embody Workday culture of integrity, innovation and fun. We are the AI/ML services team at Workday!
We are looking for individuals passionate about Creating and Operationalizing Machine Learning assets and. who take pride in running one of the best Machine Learning operations in the industry!
We are seeking a passionate and visionary leader to lead our Machine Learning (ML) Engineering and Operations Team. This role is pivotal in driving the technical strategy and execution of our AI initiatives aimed at accelerating Workday’s mission. You will be responsible for leading a geographically diverse and highly impactful team of ML engineers, analysts focusing on user experience, applied research, ML platform development and Operations.
About the Role
Responsibilities include :
- Strategic Vision: Develop and execute a clear technical roadmap for the ML platform, aligning with Workday's mission and business objectives. Continuously innovate and drive the adoption of AI technologies to enhance ML product experiences for internal end users
- Collaborate with data science product owners on end to end development and deployment of machine learning models including data preprocessing, feature engineering, model training, model evaluation, and model integration into production systems. Additionally implement and manage model versioning, tracking, and monitoring systems
- Collaborate closely with cross-functional teams including product managers, designers, and other engineering teams to ensure seamless integration of AI capabilities into business applications like SFDC, Gainsight, Market, Enterprise Data Hub.
- Foster a culture of collaboration, innovation, and continuous learning within the ML Engineering and Operations Team
- Set and maintain a high bar for technical excellence, ensuring the team follows best practices in software development, machine learning, and platform architecture.
- Establish team wide broad understanding of emerging scientific trends and techniques in MLOps, privacy, interpretability, explainability, risk management, bias and fairness, hallucinations, etc.
- Broadly set vision and act as technical/scientific advisor for how to improve our Enterprise DS practice, driving more value from data, via a combination of development programs, risk management processes, community culture, streamlining best practices, and similar initiatives
- Drive assessment of risk and opportunities for Generative AI applications, and create programs to ensure we experiment with integrity and speed
- Help define and measure technical capabilities such as Machine Learning Operations (MLOps), High Performance Engineering, etc., and create programs and practices to drive adoption of best practices.
- Help collect, curate, and refine best scientific practices across the enterprise, developing common documentation, knowledge sharing programs, training curricula, and development programs.
- More importantly, create a culture of trust, integrity and collaboration as default mode of operations.
- Reminder : 'Fun' is a core value in this team and at Workday!
We'd love to hear from you if you have:
- Significant experience in building and leading high-performing engineering teams, with a focus on AI/ML platform development and applied research. Strong understanding of Large Language Models (LLMs) , Data Science statistical concepts around classification, regression , Baysian network and time series using both shallow and deep learning techniques.
- Deep domain knowledge and understanding of machine learning frameworks, data pipelines, and platform architecture. Experience with natural language processing and generation is a plus.
- Excellent collaboration and communication skills, able to work effectively across disciplines and levels of the organization.
- Ability to thrive in a fast-paced, dynamic startup environment. Comfortable taking calculated risks and experimenting with new approaches.
- Specialist in Recruiting, mentoring, and retaining high-performing team(s) of AI/ML engineers, while fostering a culture of collaboration, innovation, and continuous learning.
- Minimum of 5+ years of proven track record leading ML engineering teams, with proven expertise in AI, including generative AI, machine learning, and enterprise / PaaS environments. Experience in multiple AI technologies, services and products, as well as legal and privacy requirements faced by organizations wanting to build AI experiences
- Expertise in software engineering best practices including coding standards, code reviews, SCM, CI, build processes, testing, and operations
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: $224,200 USD - $336,300 USD
Additional US Location(s) Base Pay Range: $179,000 USD - $336,300 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.
Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!