MLOps Engineering Manager

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.

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About the Team

This is an opportunity to be part of a growth team focused on MLOps. We build ML capabilities into our products, and you would be building part of the next generation of Workday technology. We believe predictive products can be as ground-breaking to the next interation of technology as mobile was to the last.

About the Role

We are seeking a highly skilled and experienced Machine Learning Manager to lead our dynamic team of machine learning engineers. The ideal candidate will be a hands-on technical leader with a consistent track record of building and deploying machine learning platforms and integrating them with other services. You will be responsible for driving the development and implementation of our machine learning strategy, ensuring the delivery of high-quality, scalable, and robust solutions.

Responsibilities:

• Lead and develop a team of software development engineers, fostering a collaborative, innovative environment.

• Drive the design, development, and deployment of end-to-end machine learning systems, from data ingestion and preprocessing to model training, evaluation, and deployment.

• Oversee the building/development and maintenance of our ML platform, ensuring its scalability, reliability, and performance.

• Lead the integration of machine learning solutions with other company services and systems.

• Collaborate with multi-functional teams, including product management, data engineering, and software development, to define project requirements and deliver solutions that meet business needs.

• Stay up-to-date with the latest advancements in machine learning, cloud computing, and related technologies, and drive the adoption of standard methodologies.

• Ensure the quality, security, and compliance of all machine learning solutions.

• Mentor and develop team members, providing technical guidance and fostering their professional growth.

• Manage project timelines, resources, and budgets effectively.

• Contribute to the overall AI/ML strategy of the organization.

About You

Basic Qualifications:

• Bachelor's degree in Computer Science, Machine Learning; Master's degree preferred.

• Minimum of 5 years of experience in a management role, leading machine learning or software engineering teams.

• Minimum of 10 years of hands-on experience in software engineering, with a strong focus on machine learning.

• Deep understanding of machine learning principles, algorithms, and techniques.

• Extensive experience with cloud platforms (e.g., AWS, GCP), including machine learning services (e.g., SageMaker, Vertex AI, Databricks).

• Proven experience with data engineering concepts and tools, including data warehousing, ETL processes, and big data technologies (e.g., Spark).

• Proficiency in Python and experience with machine learning libraries and frameworks (e.g.,PyTorch, TensorFlow, scikit-learn).

• Proven understanding of software development standard processes, including version control (Git), CI/CD, and testing.

• Strong experience with containerization and orchestration technologies (e.g., Docker, Kubernetes).

• Experience with data platforms and databases (SQL and NoSQL).
   

Other Qualifications:

• Excellent communication, collaboration, and leadership skills.

• Strong problem-solving and analytical abilities.

• Ability to thrive in a fast-paced, dynamic environment.

• Proven ability to deliver high-quality machine learning solutions in a production setting.

• Experience with MLOps practices and tools, ideally Kubeflow ecosystem.

• Contributions to open-source machine learning projects.

• Experience with specific machine learning domains (e.g., natural language processing, recommendation systems)

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: CAN.ON.Toronto

Primary CAN Base Pay Range: $132,000 - $198,000 CAD

Additional CAN Location(s) Base Pay Range: $132,000 - $198,000 CAD

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!