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Workday

Software Development Engineer for Machine Learning

Posted 16 Days Ago
Be an Early Applicant
In-Office
Vancouver, BC
Mid level
In-Office
Vancouver, BC
Mid level
As a Software Development Engineer for Machine Learning, you will build platforms and services leveraging ML, develop APIs/microservices, and work closely with ML engineers to improve core Workday products.
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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 a great opportunity to join the Machine Learning organization at Workday! Our AI platforms power all core Workday products, serving 70 million users under contract and generating more than 800 billion transactions per year. Our multi-functional team works on building next generation ML solutions for a wide array of problems using the world’s largest and cleanest HR and Finance dataset.
Our team flourishes with collaboration, inclusivity, and innovation. We are looking for individuals who are curious, agile and meticulous. Join us as we transform the way millions of people work!

About the Role

As a Software Development Engineer, you will be building platforms and services that leverage machine learning to modernize and simplify how users interact with Workday. You will work on interesting projects including information retrieval, recommendations, and Agentic services. As a Software Engineer, you will also be closely working with Machine Learning Engineers to deliver ML features across Workday’s product ecosystem and use software and data engineering stacks to enable training, deployment, and lifecycle management of various ML models. You will be responsible for the design, implementation, productionization and observability of any features you work on. Additionally, you will develop and deploy new APIs/microservices using Docker/Kubernetes at scale and leverage Workday’s vast computing resources on rich datasets to deliver transformative value to our customers. Sound like your kind of challenge?

About You

In addition to contributing to feature and service development, you must have an approach of continuous improvement and passion for quality, scale, and security. You must be curious and prepared to question or challenge choices and practices where they don't make sense to you or could be improved. You also should have a product-focused approach and strong intuition around how ML can drive a better customer experience. Lastly, a strong sense of ownership and teamwork are critical to succeed in this role.

Key Responsibilities:

  • Build, deploy, tune, and optimize Python and Spark-based ETL pipelines for collecting, joining, transforming, and loading data used for model training and inference
  • Build, deploy, monitor, and maintain secure, RESTful web services in Python and Kubernetes that power our agents and recommendations
  • Design and implement multi-tenant runtime architectures that enable fast inference, scale to millions of users, and integrate with existing Workday components
  • Understand and address complex system design challenges related to microservices, including caching, sharding, observability, and event-based architecture
  • Work effectively with teammates on code reviews, knowledge shares, hackathons, etc.
  • Collaborate with other platform teams to improve shared infrastructure and components
  • Triage and address alerts and production issues as part of an on-call rotation

Basic Qualifications

  • Bachelor’s (Master’s or PhD preferred) degree in engineering, computer science, physics, math, or equivalent
  • Strong proficiency in Python
  • 3+ years of professional experience building scalable systems and optimizing performance of large-scale web services 
  • 2+ years of professional experience building ETL pipelines and data wrangling using industry-standard tools like Pandas, PySpark, and SageMaker to build scalable data pipelines
  • 2+ years of professional experience building horizontally scalable, RESTful web applications
  • 2+ years of professional experience scaling services with containerization technologies like Kubernetes and Docker
  • 2+ years of professional experience with cloud computing platforms (e.g. AWS, GCP, etc.)

Other Qualifications:

  • Takes ownership and delivers complete products, balancing craftsmanship with the need to ship to customers
  • Professional experience in building information retrieval systems and/or recommendation systems
  • Professional experience in machine learning and deep learning frameworks and toolkits such as PyTorch, TensorFlow, and Sklearn
  • Professional experience with Python and supporting numeric libraries, with experience in shipping production code and models
  • Experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases
  • Professional experience in independently solving ambiguous, open-ended problems.
  • Ability to design and implement creative workarounds for unforeseen obstacles
  • Standout colleague, strong communication skills, with experience working across functions and teams
  • Ability to teach, mentor, and lead through influence


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.BC.Vancouver

Primary CAN Base Pay Range: $106,400 - $159,600 CAD

Additional CAN Location(s) Base Pay Range: $106,400 - $159,600 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!

Top Skills

AWS
Docker
GCP
Kubernetes
Pandas
Pyspark
Python
PyTorch
Sagemaker
Sklearn
Spark
TensorFlow

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