Senior ML Engineer

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

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About the Role

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About You

Basic Qualifications

8+ years experience in machine learning development, researching, developing, and implementing advanced machine learning models and techniques.

[Insert years] experience and proficiency in areas such as deep learning, natural language processing, or computer vision, utilizing frameworks and libraries such as [insert frameworks and libraries].

Bachelor’s degree in a relevant discipline such as Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related discipline, or equivalent practical experience; a PhD in a relevant discipline is also welcome.

Other Qualifications

Strong ability in Data Processing, including [insert specific advanced techniques or tools], to design and implement robust data pipelines for machine learning.

Solid knowledge of Data Science principles and their application in [insert specific advanced areas like causal inference or time series analysis].

Experience leading Exploratory Data Analysis (EDA) efforts to [insert specific actions like deriving key insights or validating assumptions].

Strong understanding of Feature Engineering methods to [insert specific actions like developing novel features or handling complex data issues].

Solid knowledge of a wide range of Machine Learning algorithms and their application in [insert specific complex problem domains].

Experience leading Model Building processes and [insert specific advanced modeling techniques].

Deep understanding of the Model Development lifecycle and experience in [insert specific advanced stages like model monitoring or retraining strategies].

Working knowledge of Model-Based Design (MBD) concepts and their application in [insert relevant complex application areas].

Strong proficiency in Python (Programming Language) and a broad range of libraries for data science and machine learning, such as [insert specific advanced libraries].

Good understanding of Software Development principles and experience in deploying and scaling machine learning models in production environments.

Strong Team Collaboration skills and the ability to mentor and guide other team members.

Workday Pay Transparency Statement (For EU Locations Only)

Listed below is the base salary range applicable to this position. Workday pay ranges (and the precise pay offered to the successful candidate) are based on a number of objective criteria such as relevant experience and skills, and educational qualifications, level of responsibility, demands of the role, work location and business need. 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 awarded by Workday Inc. For more information regarding Workday’s comprehensive benefits, please click here.

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 [email protected], as far in advance as possible.

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