Machine Learning Engineer, Workday

CA$120-180k

AWS
Docker
Kubernetes
GCP
Python
Tensorflow
Pandas
PyTorch
Mid and Senior level
Toronto
Vancouver
Workday

Enterprise management cloud platform

Open for applications

Workday

Enterprise management cloud platform

1001+ employees

B2BHRInternal toolsAnalyticsFinancial ServicesCloud Computing

Open for applications

CA$120-180k

AWS
Docker
Kubernetes
GCP
Python
Tensorflow
Pandas
PyTorch
Mid and Senior level
Toronto
Vancouver

1001+ employees

B2BHRInternal toolsAnalyticsFinancial ServicesCloud Computing

Company mission

To provide an all-in-one management cloud solution for the rapidly changing business requirements of the modern world.

Role

Who you are

  • In addition to contributing to feature and service development, you must have a mindset of continuous improvement, 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 mindset and strong intuition around how ML can drive a better customer experience
  • Lastly, a strong sense of ownership and teamwork are key to succeed in this role
  • Bachelor’s (Master’s preferred) degree in engineering, computer science, physics, math or equivalent
  • 3+ yrs experience as a member of a data science or machine learning science, machine learning engineering, or other relevant software development team
  • Proficiency in Python and supporting numeric libraries, with experience in shipping production code and models
  • Experience in machine learning and deep learning frameworks & toolkits such as Pytorch, Tensorflow, and Sklearn
  • Proven theoretical and practical understanding of statistical analysis and machine learning algorithms, natural language processing, especially for supervised, unsupervised and self-supervised methods
  • Experience with generative models, large language models, and transformer based deep neural networks
  • 2 or more years experience building applied machine learning products, including taking a product through applied research, design, implementation, production, and production based evaluation
  • Execution of projects for products handling large-scale, complex data sets, data modeling, and productizing algorithms
  • 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 communication 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 solve problems independently

What the job involves

  • 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 solve complex problems and influence machine learning and application development across Workday
  • 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, you will help develop tailored experiences for every user powered by advanced Large Language Models (LLMs), personalization, and predictive analysis
  • You will work closely with other ML engineers and software developers to deliver ML solutions that enable ML powered search and user experience across Workday’s product ecosystem
  • You 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
  • You will develop new APIs/microservices and deploy them using docker/kubernetes at scale
  • You 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
  • 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
  • Own 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

Our take

Workday is a cloud-based software vendor that provides management of workforces and finances. The company uses a single database for workforce management and financial management to offer integration and optimize business intelligence across companies. It has added to the packages and tools it offers over the years, providing analytic options that allow companies to combine third-party data with information collected by Workday.

Workday has acquired and paired up with many other companies to keep expanding its offering. In 2021, it purchased the employee feedback platform Peakon in response to the growing need for managers to be able to survey workers and collect satisfaction data without face-to-face meetings. The company has also bought and developed many financial tools and HR management tools.

The company’s goal is to provide end-to-end back office services and while there are other providers, such as UKG Pro and Ceridian HCM, Workday’s broad offering helps them to stand out. Though it faced a tough global market in 2023 and has shed some of its headcount, Workday has seen a 6.5% gain in value in the first quarter of 2024. It is now focusing on growth and developing the AI capabilities of its platform. .

Kirsty headshot

Kirsty

Company Specialist

Insights

Top investors

Many candidates hear
back within 2 weeks

16% employee growth in 12 months

Company

Funding (last 2 of 5 rounds)

Oct 2011

$85m

SERIES F

Apr 2009

$75m

SERIES E

Total funding: $215.3m

Company benefits

  • Company equity
  • Vision and dental insurance
  • Work from home opportunities
  • Health insurance
  • Virtual primary care
  • Flexible time-off policy
  • Global mental health resources
  • Global dedicated on-site clinical counselors
  • Global well-being days
  • $25k fertility/family planning benefits
  • North Star financial wellness
  • Retirement funds and matching

Company values

  • Employees - Most fundamentally, people are the core of our business. Without them, we would not have a business. We hire the best and expect great accomplishments
  • Customer service - Every investment and decision we make has our customers in mind, and we pull out all stops to make the satisfaction of our customers paramount
  • Innovation - We aim for innovation not only in our development organization but also in the way we approach all aspects of our business
  • Integrity - We say what we mean, and mean what we say. We stick to our commitments, treat everyone equitably, and communicate openly and honestly
  • Fun - We also feel it’s important to have a sense of humor. We like to laugh—it makes our work that much more enjoyable. We also invest in community and company events that help our employees and their families feel a connection to Workday beyond business as usual
  • Profitability - Long-term economic success is what helps us provide employees and customers with the best productivity tools, solutions, and services. While important, profitability is not why we exist. Simply put, at Workday we exist to make and provide great products and services

Company HQ

Pleasanton, CA

Leadership

Worked for Morgan Stanley for 3 years and took a Stanford MBA, before spending almost 6 years at Oracle as SVP. Co-founded Workday in 2005 while working as a Greylock Advisory Partner.

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