Principal Software Development Engineer for Machine Learning

Workday, Inc.; Toronto; On-site; CAD 156,000 - 236,000; Full time

Job summary

A leading enterprise software company is seeking a Principal Software Development Engineer for Machine Learning in Toronto, Ontario. The role focuses on designing and deploying scalable AI systems and data pipelines while utilizing Python, Kubernetes, and cloud platforms. Candidates should have 8+ years of development experience, with a strong background in MLOps and machine learning solutions. This position offers competitive compensation with a salary range of CAD $156,800 - $235,200.

Qualifications

• 8+ years of experience in Software Development.
• 4+ years of experience in Python and data pipeline development.
• Validated experience deploying production services using MLOps.

Responsibilities

• Architect and implement scalable AI systems.
• Lead development and deployment of ML infrastructure.
• Provide technical leadership and promote software development best practices.

Skills

Python

Machine Learning

Data Pipeline Development

Kubernetes

Cloud Platforms (AWS, Azure, GCP)

Education

Bachelor's degree in Computer Science or Engineering

MS / PhD in relevant field

Tools

Spark

Docker

PostgreSQL

Redis

Job description

About the Role

As a Principal Software Development Engineer for Machine Learning, you will be a pivotal technical contributor, working closely with machine learning engineers to architect, build, and deploy robust, scalable, and performant AI systems across Workday's product ecosystem. You will play a key role in transforming innovative ML research into production-ready solutions, primarily agentic AI capabilities encompassing planning, reasoning, and action execution frameworks.

Your primary focus will be to :

Own the architectural design and implementation of sophisticated AI systems and agentic AI capabilities, with a focus on advanced patterns such as tool calling, supervisor agents, multi-agent architectures, and human-in-the-loop integration. Ensure solutions are highly scalable, performant, and resilient in production environments, defining technical roadmaps and standard methodologies for ML system development and MLOps.

Build and Deploy Core ML Infrastructure : Architect, implement, and deploy secure, RESTful web services in Python and Kubernetes. Design and build robust, multi-tenant runtime architectures enabling fast inference and scaling to millions of users, seamlessly integrating with existing Workday components and using cloud deployment standard methodologies.

Develop and Optimize Data Pipelines : Lead the development and deployment of Python and Spark-based data pipelines for collecting, joining, transforming, and loading large-scale datasets essential for model training and inference. Focus on efficiency, reliability, and data quality.

Provide technical leadership and guidance to fellow engineers, fostering a culture of engineering excellence, advocating for software development standard methodologies, and participating in design reviews and code quality initiatives.

You will also :

Collaborate multi-functionally to translate requirements into technical designs, taking ownership of creative, high-quality solutions.

Apply and continuously advance industry-standard software engineering practices, including automation, observability, scalability, and MLOps, to deliver clean, maintainable, and testable code.

About You

Bachelor's degree in Computer Science, Engineering, or a related technical field.

8 or more years of experience in production-level Software Development.

4 or more years of experience in Python, with a consistent track record of shipping production code and systems.

4 or more years of experience building scalable data pipelines and working with large-scale datasets.

4 or more years of validated experience deploying production services to cloud platforms (e.g., AWS, Azure, GCP) and using containerization technologies (e.g., Docker, Kubernetes) for MLOps.

Other Qualifications :

MS / PhD degree in a relevant field, such as Computer Science or Engineering.

Deep technical expertise in the engineering, deployment, and MLOps of advanced machine learning solutions (e.g., generative models, LLMs, RAG, and AI agents), coupled with a strong understanding of scalable distributed systems, performance optimization, database technologies (e.g., PostgreSQL, Redis), and robust API development.

Validated algorithmic thinking and a tracproven historydesigning, implementing, and analyzing efficient algorithms for complex problems.

Demonstrated ability to build flexible, reusable, and well-documented software components, with comprehensive experience in code testing strategies (unit, integration, end-to-end) in a continuous deployment environment. Strong sense of ownership and a proven ability to deliver high-quality, finished products efficiently.

Excellent communication and collaboration skills, emphasizing team collaboration, knowledge-sharing, and delivering customer impact.

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 .

Primary Location : CAN.BC.VancouverPrimary CAN Base Pay Range : $156,800 - $235,200 CADAdditional CAN Location(s) Base Pay Range : $156,800 - $235,200 CAD