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Senior Software Development Engineer-MLOps

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.

At Workday, we value our candidates’ privacy and data security.  Workday will never ask candidates to apply to jobs through websites that are not Workday Careers. 

  

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About the Team

Workday is the cloud-based SaaS company providing industry-leading software for HR, financials, workforce planning and employee learning to more than 40% of the Fortune 500. We are the Machine Learning Product team at Workday. Our focus is on the application of machine learning and statistical analysis to Workday’s products to serve our end users. We use diverse datasets to build data-driven products, which help the world’s largest organizations uncover insights and make strategic decisions about their people, finances, and business. We routinely work on data with high velocity, volume and variety, and we employ a modern machine learning distributed computing and big data software stack to deal with these challenges.
At Workday, we truly care about our people, that’s why we rank as the top 5 best places to work. To learn more about Workday ML, check out this video:
https://bit.ly/34efgyg

About the Role

This is an opportunity to be part of a growth team focused on MLOps. We build ML capabilities into our products, and you would be building part of the next generation of Workday technology. We believe predictive products can be as ground-breaking to the next generation of technology as mobile was to the last.

As a Senior Software Engineer, you will help develop ML powered features and experiences for every user across our HR & Talent product portfolio. You will work closely with ML engineers and other software teams to deliver critically important infrastructure and software frameworks that enable machine learning across Workday’s product ecosystem. You will apply modern MLOps, CloudOps, and data engineering stacks to enable development, training, deployment, and lifecycle management of a variety of ML capabilities; supervised and unsupervised, deep learning and classical. You will be responsible for the design & development of new APIs/microservices and deploy them using Python, Terraform and Kubernetes at scale.

You will use Workday’s vast computing resources on rich, exclusive datasets to deliver value that transforms the way our end-users experience WD. 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 people.

In this role, you would:

  • Work with multi-functional teams to deliver scalable, secure and reliable solutions
  • Building MLOps platform primarily using Kubeflow, and other ML ecosystem framework and services for building a unified ML Development experience
  • Effectively engage with data scientists, ML engineers, PMs and architects in requirements elaboration and drive technical solutions
  • Own and develop cloud-based services from end to end including infrastructure as code
  • Design and build software solutions for efficient organization, storage and retrieval of data to enable substantial scale
  • Understanding cloud computing and security to build robust cloud infrastructure and solutions for ML teams
  • Build systems and dashboards to monitor service & ML health
  • Lead in architecture reviews, code reviews and technology evaluation
  • Research, evaluate, prototype and drive adoption of new ML tools with reliability and scale in mind

About You

Basic Qualifications

  • Solid experience as a Software Development Engineer in ML domain- 5+ years’ experience with a Master’s or higher or 6+ years with a Bachelor’s in Computer Science or Computer Engineering or equivalent
  • 4 year’s experience designing, implementing, and maintaining robust MLOps services for deploying, monitoring, and scaling machine learning development primarily using Kubeflow or similar platforms
  • Professional experience in building web applications and microservices and API design
  • Solid understanding on how to implement and manage CI/CD workflows to automate testing, integration, and delivery of machine learning components
  • Experience in supporting large Kubernetes networks in production
  • 6 or more years of cloud programming experience preferably in Python or Go
  • Experience with running and maintaining ML platforms such as: Databricks, Sagemaker, and or VertexAI

Other Qualifications

  • Implementation and operation of distributed systems
  • Stay abreast of industry trends and emerging technologies, providing recommendations for continuous improvement of our DevOps and machine learning practices
  • Troubleshoot and resolve performance bottlenecks, system outages, and other operational issues in collaboration with the ML engineering teams
  • Ensure the security and compliance of machine learning platforms, implementing best practices for encryption, data protection and access controls
  • Optimize public cloud-based infrastructure (AWS, GCP) to support the computational requirements of machine learning workloads
  • Experience in managing relevant tools like Databricks and Sagemaker to perform efficient computation and management of large-scale data lakes
  • Experience of data and/or ML systems with ability to think across layers of the stack
  • Develop and maintain monitoring and alerting systems for proactively identifying and addressing issues within the machine learning infrastructure
  • Experience in leading or mentoring other team members


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.ON.Toronto

Primary CAN Base Pay Range: $132,800 - $199,200 CAD

Additional CAN Location(s) Base Pay Range: $132,800 - $199,200 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!

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Average salary estimate

$166000 / YEARLY (est.)
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$132800K
$199200K

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What You Should Know About Senior Software Development Engineer-MLOps, Workday

Welcome to Workday, where we're on an exciting journey to redefine the enterprise software landscape! We’re on the lookout for a Senior Software Development Engineer specializing in MLOps to join our innovative Machine Learning Product team right here in Toronto, Ontario. Your role will be pivotal in integrating machine learning capabilities into our HR and Talent product portfolio. Imagine developing cutting-edge features that enhance user experiences for organizations around the globe! With a focus on systems reliability and scalability, you’ll be using tools like Python, Terraform, and Kubernetes to deploy microservices that drive our technology forward. You will collaborate with a talented group of ML engineers and other talented professionals to elevate how we leverage data in our products, maintaining our commitment to employee-centric values. Your work will directly impact the lives of millions, using our rich data sets to help businesses plan effectively while being backed by a supportive and growth-oriented culture. At Workday, we believe in growth, creativity, and balance—that's why we offer flexible working arrangements so you can find the blend of in-office and remote work that works best for you. Join us and help build MLOps solutions that empower our users and revolutionize how enterprises function. Together, we can make every workday brighter!

Frequently Asked Questions (FAQs) for Senior Software Development Engineer-MLOps Role at Workday
What are the main responsibilities of a Senior Software Development Engineer-MLOps at Workday?

As a Senior Software Development Engineer-MLOps at Workday, you'll be responsible for designing and implementing machine learning solutions, building MLOps platforms using Kubeflow, and collaborating with multi-functional teams to develop scalable cloud-based services. You will also engage with data scientists to craft technical solutions while ensuring the reliability and performance of ML infrastructure.

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What qualifications do I need for the Senior Software Development Engineer-MLOps position at Workday?

To qualify for the Senior Software Development Engineer-MLOps role at Workday, you'll need at least 5+ years of experience in the machine learning domain, a solid educational background in Computer Science or Engineering, and expertise in Kubernetes and MLOps services. Familiarity with cloud computing, Python, and CI/CD workflows is also essential to succeed in this position.

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How does Workday support the career development of a Senior Software Development Engineer-MLOps?

At Workday, we prioritize the professional growth of our employees, including Senior Software Development Engineers specializing in MLOps. We provide a collaborative environment for continuous learning, mentorship, and the opportunity to stay abreast of emerging technologies. You will also have chances to lead architecture reviews and share your knowledge with peers.

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What technologies will I work with as a Senior Software Development Engineer-MLOps at Workday?

In this role, you'll tackle modern MLOps challenges using technologies like Kubeflow, Python, Terraform, and Kubernetes. Additionally, you'll work with cloud platforms such as AWS and GCP to manage large datasets and streamline ML development and deployment.

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What is the work culture like at Workday for a Senior Software Development Engineer-MLOps?

Work at Workday is centered around a people-first culture, where collaboration, creativity, and flexibility thrive. As a Senior Software Development Engineer-MLOps, you can expect a supportive environment that values transparency and encourages you to bring your authentic self to work while contributing toward making every workday better.

Join Rise to see the full answer
Common Interview Questions for Senior Software Development Engineer-MLOps
Can you describe your experience with MLOps frameworks in your previous roles?

In answering this question, highlight your specific experiences with different MLOps frameworks, particularly Kubeflow. Discuss projects where you implemented these frameworks, detailing the challenges faced and the solutions you employed to overcome them. Be sure to cover how these experiences prepare you for the Senior Software Development Engineer-MLOps role at Workday.

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What is your approach to ensuring the reliability of machine learning services?

Focus on your methodologies in monitoring and maintaining machine learning services, such as implementing robust testing protocols, building alerts, and using dashboards for health monitoring. Discuss your experiences in troubleshooting issues and optimizing infrastructure to support ML workloads.

Join Rise to see the full answer
How do you handle collaboration with data scientists and machine learning engineers?

Emphasize the importance of open communication and understanding each role's challenges. Share examples where collaboration helped in elaborating requirements and driving technical solutions effectively, showcasing your ability to work with cross-functional teams.

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What tools and technologies have you used for CI/CD in machine learning projects?

Detail your experience with CI/CD tools that facilitate automation in machine learning workflows, such as Jenkins, GitLab CI, or CircleCI. Give explanations about how you have used these tools to streamline build and deployment processes for ML components.

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Describe a significant challenge you faced while deploying machine learning models.

Share a specific example of a challenge, such as scaling the model for production use or integrating it with existing infrastructure. Discuss how you resolved the issue, ensuring that you align your response with the skills and knowledge relevant to the work at Workday.

Join Rise to see the full answer
How do you stay current with the latest trends in MLOps and machine learning technology?

Point out your strategies for continuous learning, such as attending industry conferences, participating in online courses, or engaging in community forums. Mention any relevant blogs or publications you follow to keep yourself updated on MLOps advancements.

Join Rise to see the full answer
What is your experience with building microservices for machine learning applications?

Discuss your experience with designing and implementing microservices architectures, focusing on ML applications. Elaborate on how microservices can improve scalability and ease the deployment of machine learning components in cloud environments.

Join Rise to see the full answer
Can you provide an example of a successful project you completed in a previous MLOps role?

Select a project that had a significant positive outcome and describe the problem it solved. Emphasize your role in the project, the technologies used, and the impact it had on the stakeholders or the business, ensuring the project highlights your qualifications for Workday.

Join Rise to see the full answer
How do you approach security considerations when developing ML services?

Highlight your knowledge of security best practices in cloud computing, especially concerning data protection and access controls. Discuss how you implement measures to ensure compliance and secure ML platforms during development and operational phases.

Join Rise to see the full answer
Why do you want to work as a Senior Software Development Engineer-MLOps at Workday?

Craft a thoughtful answer that intertwines your aspirations with Workday’s mission and culture. Speak about your admiration for the company’s commitment to a people-first culture, opportunities for innovation, and how your background aligns perfectly with the role's responsibilities.

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Inclusive & Diverse
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Mission Driven
Diversity of Opinions
Work/Life Harmony
Transparent & Candid
Growth & Learning
Fast-Paced
Collaboration over Competition
Take Risks
Friends Outside of Work
Passion for Exploration
Customer-Centric
Reward & Recognition
Feedback Forward
Rapid Growth
Medical Insurance
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Maternity Leave
Mental Health Resources
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Paternity Leave
Fully Distributed
Flex-Friendly
Some Meals Provided
Snacks
Social Gatherings
Pet Friendly
Company Retreats
Dental Insurance
Life insurance
Health Savings Account (HSA)

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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