Principal, Machine Learning Engineer (workday)
Job posting number: #161369 (Ref:JR-0091632)
Job Description
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 Team
We're working on making machine learning core to Workday's products by building data products and auto-ml models that can be scaled out to hundreds of use cases within Workday. 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. You will tackle sophisticated problems and influence machine learning and application development across Workday. Our team is passionate about teaching and learning, so be eager to share your expertise and learn from us. Join us as we change the way millions of people work.About the Role
We're building ML powered Search and Generative AI services and platforms to modernize how users interact with workday - adding ease, intelligence and efficiency to everyday interactions. All of these capabilities are designed to be applied across a wide range of applications within Workday.
As a machine learning engineer, the ideal candidate will help develop tailored experiences for every user powered by sophisticated Large Language Models (LLMs), personalization, and predictive analysis. They will work closely with other ML engineers and software developers to deliver ML solutions that enable ML search and user experience across Workday’s product ecosystem. They will apply current software and data engineering stacks to enable training, deployment, and lifecycle management of a variety of ML models; supervised and unsupervised, deep learning and classical. They will develop new APIs/microservices and deploy them using docker/kubernetes at scale. They will use Workday’s vast computing resources on rich, exclusive 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. Sound like your kind of challenge?
Key Responsibilities:
Own exploration, design and execution of advanced ML models, algorithms and frameworks that deliver value to our users.
Preprocess and clean large amounts of unstructured text data to ensure quality and consistency for Natural Language Processing (NLP) and other ML model training.
Engineer relevant features from textual data to facilitate accurate model predictions and classification.
Apply machine learning techniques including LLMs, deep learning including generative models, natural language understanding, sentiment analysis, topic modeling, and named entity recognition to analyze large sets of HR-related text data, and design and launch pioneering cloud based machine learning architectures.
Train, validate, and fine-tune machine learning models using large-scale datasets to achieve robust performance.
Be responsible for the performance, scalability, metric based deployed evaluation, and ongoing data driven enhancements of your products.
Collaborate across teams to deliver your products through Workday end user applications.
Be given autonomy and ownership over your work, but with the support of the entire organization.
Keep abreast of the latest advancements in NLP research, techniques, and tools.
Have extraordinary opportunities for career growth and learning in a fast-growing, forward-looking company.
About You
Basic Qualifications for Principal:
Bachelor’s (Master’s preferred) degree in engineering, computer science, physics, math or equivalent.
Validated theoretical and practical understanding of statistical analysis and machine learning algorithms, NLP, especially for supervised, unsupervised and self-supervised methods.
View Orignal JOB on: italents.netExperience with generative models, LLMs, and transformer based deep neural networks.
7 or more years of proven experience of the following:
Developing, deploying, and supporting high-performance systems in production
Industry tools used to build scalable machine learning systems, such as AWS, SQL, Elasticsearch/Open Search, Kubernetes, Docker and/or Spark
Delivering applied machine learning products, including taking a product through design, implementation, and to production
Developing Machine Learning driven features with Python (including NumPy, SciPy, Pandas), JVM, and Linux
Basic Qualifications for Senior:
Bachelor’s (Master’s preferred) degree in engineering, computer science, physics, math or equivalent.
Validated theoretical and practical understanding of statistical analysis and machine learning algorithms, NLP, especially for supervised, unsupervised and self-supervised methods.
Experience with generative models, LLMs, and transformer based deep neural networks.
5 or more years of proven experience of the following:
Developing, deploying, and supporting high-performance systems in production
Industry tools used to build scalable machine learning systems, such as AWS, SQL, Elasticsearch/Open Search, Kubernetes, Docker and/or Spark
Delivering applied machine learning products, including taking a product through design, implementation, and to production
Developing Machine Learning driven features with Python (including NumPy, SciPy, Pandas), JVM, and Linux
Other Qualifications:
Experience with data engineering and data wrangling using e.g. Pandas and PySpark.
Familiarity with LLMs such as Llama, different GPT models, and their applications in real-world scenarios.
Exposure to advanced techniques such as reinforcement learning, imitation learning, and graph neural networks.
Experience with cloud computing platforms (e.g. AWS, GCP) and containerization technologies (e.g. Docker).
Standout colleague, strong interpersonal skills, with experience working across functions and teams.
Bonus points for relevant PhD and/or machine learning related research publications.
Resilience to obstacles, and ability to tackle problems independently.
Posting End Date: 12/16/24
The application deadline for this role is the same as the posting end date stated.
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.CO.BoulderPrimary Location Base Pay Range: $192,000 USD - $288,000 USDAdditional CAN Location(s) Base Pay Range: $173,600 - $260,400 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.
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