Senior Machine Learning Engineer - Data Pipelines and Analytics Architect

Your workdays are brighter here. At Workday, it all began with a conversation over breakfast. Our founders met at a sunny California diner and devised a plan to revolutionize the enterprise software market. What distinguished us as we rose was our culture, a culture driven by the principle of prioritizing our people. Ever since, the happiness, development, and contribution of every Workmate have been central to our identity. Our Workmates believe a healthy, employee-centric, and cooperative culture is the essential recipe for success in business. Consequently, we take care of our people, our communities, and our planet whilst still remaining profitable. Feel free to shine in your own unique way, don't hide who you are. You can feel the energy and passion, it's what makes us unique. Inspired to make workdays brighter for everyone and evolve with us to the next stage of our growth journey? Bring your brightest self and have a brighter workday here. About the Team Join Workday’s Talent products organization and assist us in building amazing companies through great people. Talent is a product pillar that delivers applications and services enabling organizations to hire, retain, and unlock the maximum potential of their employees. In the Talent ML team, we contribute to the Pillar's success by continuously enhancing our machine learning services and obtaining valuable insights from data of tens of millions of users through conducting experiments. About the Role We are developing a new scalable recommendation service and data processing pipelines and are looking for someone experienced in delivering Machine Learning products end-to-end. As a technical leader on the team, you'll be encouraged to implement best practices in MLOps, design, and build ETL pipelines, recommendation services, and experiments for service, algorithm, and model improvement. You will also mentor junior engineers in all aspects of the Machine Learning Engineering domain. Key Responsibilities: - Define and implement best MLOps practices on the team - Contribute to the team’s roadmap in features development, data acquisition, processing, metrics, experimentation, and data science - Guide Product Managers on integrating ML capabilities into their applications - Be responsible for the performance, scaling, and continuous improvements of systems owned by the team - Give and receive PR feedback that aids you and your colleagues in refining their practices and learning from each other - Independently identify ML opportunities and suggest solutions to leadership - Own design documents for new ML components and enhancements to existing components About You You should enjoy continuous learning and be able to cope with setbacks positively, especially when your ideas are proven wrong. You should have a burning desire to clearly answer the “Why?” question for each project. You should be willing to contribute to all layers of ML feature development, from data acquisition and cleanup, model training to UX/UI flows. Essentially, if you enjoy working in a startup-like environment, this opportunity is for you. You need to be able to overcome challenges, whatever they may be. Our challenges include scalability and performance, feature metrics, business hypothesis testing, and analytical insights. Basic Qualifications: - Bachelor’s degree or higher in engineering, computer science, physics, math, or equivalent - Proven experience in teaching, mentoring, and leading by influence - 7 or more years of experience in delivering applied machine learning products, including managing a product through design, implementation, and production stages - 5 or more years of experience with Python (including NumPy, SciPy, Pandas, pySpark) and Linux - Experience in conducting A/B testing - Experience in communicating through data visualizations - Experience in scaling data processing for large data sets. Other Qualifications: - Resilience to obstacles and ability to solve problems independently - Experience in building standard processes for software development, such as DevOps, MLOps, CI & CD - Product-first mentality is a must. Workday Pay Transparency Statement The annualized base salary rates listed below are for the primary location and further location(s). Workday pay ranges are subject to variation depending on location. This role may be eligible for the Workday Bonus Plan or role-specific commission/bonus, as well as annual refresh stock grants. More details will be shared by recruiters during the hiring process. Compensation offers shall be based on several factors such as geography, experience, skills, job duties, and business need, among others. For further information regarding Workday’s comprehensive benefits, please click here. Primary Location: CAN.BC.Vancouver Primary CAN Base Pay Range: $144,400 - $216,600 CAD Additional CAN Location(s) Base Pay Range: $144,400 - $216,600 CAD Our Approach to Flexible Work With Flex Work, we’re combining the best of both worlds: in-person interaction and remote work. This approach allows our teams to deepen connections, maintain a strong community, and deliver their best work. We believe that flexibility can take many forms, so rather than imposing a fixed number of required in-office days each week, we spend at least half (50%) of our time each quarter in the office or field with our customers, prospects, and partners, depending on the role. This means you'll have the freedom to create a flexible schedule that suits your business, team, and personal needs, whilst being intentional about making the most of time spent together. Those in our remote "home office" roles also have the opportunity to convene in our offices for significant occasions. According 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 Workday connection about our Employee Referral process!