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Sr Machine Learning Engineer

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 TeamAre you incredibly motivated by witnessing machine learning/AI products come to life in production settings which impact tens of millions of people? As part of a global, high-growth technology company, our work supports thousands of the largest global companies and more than 30 million end users. Workday’s Machine Learning organization is bringing “AI first” products to life at every step of the Workday product offering. We’re looking for highly creative, results-focused, and deeply skilled machine learning engineers/scientists to work with us on a variety of challenges in the Human Capital Management space.About The RoleAs a Senior Machine Learning Engineer, you will research, develop and build impactful and scalable personalized recommendation systems and generative AI applications within the Human Capital Management space. You will work closely with other ML engineers, software developers and product teams to deliver ML solutions that enable personalized user experiences across Workday’s product ecosystem. You will lead projects handling everything from specification design, data collection and labeling pipelines, to model and API development, validation, deployment, and ongoing monitoring. You will use Workday’s rich datasets to deliver value that transforms the way our customers make decisions and run their business. We will challenge you to apply your best creative thinking, analysis, problem-solving, and technical abilities to make an impact on thousands of enterprises and millions of users. If this sounds like a great opportunity, we'd love to hear from you.About YouBasic Qualifications• Bachelor's degree in a relevant field, such as Computer Science, Mathematics, or Engineering.• 6+ years experience working on a data science, machine learning or related software development team.• 6+ years experience in Python and supporting numeric libraries, with experience in shipping production code and models.• 4+ years experience in machine learning and deep learning frameworks & toolkits such as Pytorch and SklearnOther Qualifications• PhD or MS degree in a relevant field, such as Computer Science, Mathematics, or Engineering. Publications in machine learning research are helpful.• Practical experience with generative models, large language models (LLM), transformer neural networks, search, recommendation systems, and graph neural networks.• Experience with cloud computing platforms (e.g. AWS, GCP), containerization technologies (e.g. Docker) and data engineering pipelines (e.g. ETL)• Experience developing and deploying machine learning solutions using large-scale datasets, including specification design, data collection and labeling, model development, validation, deployment, and ongoing monitoring.• An ability to balance mission-criticality with delivering high-quality, practical solutions. Validated perseverance in overcoming meaningful problems.Workday Pay Transparency StatementThe 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.TorontoPrimary CAN Base Pay Range: $148,000 - $222,000 CADAdditional US Location(s) Base Pay Range: $159,600 USD - $276,000 USDOur Approach to Flexible WorkWith 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!,
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Workday brings finance, HR, and planning into one system, making it possible for enterprises of all sizes to shed their disparate systems and build better businesses. We serve over 7,900 of the world’s largest companies, educational institutions, ...

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Full-time, hybrid
DATE POSTED
August 14, 2024

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