Applied Machine Learning Scientist developing Generative AI and predictive ML solutions for TD banking. Evaluating models, managing AI lifecycles, and supporting responsible implementation.
About the role
- Software Development Engineer for building scalable AI platforms at Workday. Focus on agentic AI capabilities and collaborate with senior engineers and ML researchers.
Responsibilities
- Implement AI Platforms: Develop and maintain sophisticated AI platform capabilities, focusing on patterns like tool calling, multi-agent architectures, and human-in-the-loop integrations.
- Build ML Infrastructure: Develop and deploy secure, RESTful web services using Python and Kubernetes.
- Collaborative Engineering: Participate in design reviews and code quality initiatives.
- Translate Requirements: Work with cross-functional teams to turn product requirements into functional technical designs.
- Apply MLOps Standards: Utilize industry-standard practices, including automation, observability, and CI/CD, to deliver high-quality ML solutions.
- Continuous Learning: Stay current with evolving AI/ML technologies and contribute to the team’s collective knowledge.
Requirements
- 5+ years experience in software development engineering including designing, developing, and deploying software solutions.
- 2+ years of experience in Python, with a consistent track record of shipping production code and systems.
- 2+ years of experience building scalable data pipelines and working with large-scale datasets.
- 2+ 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.
- Bachelor’s degree in a relevant field such as Computer Science, Engineering, or a related discipline, or equivalent practical experience.
- Solid ability in Algorithmic Thinking to design and implement efficient solutions for agentic system development.
- Expertise in the engineering, deployment, and MLOps of advanced machine learning solutions (e.g., generative models, LLMs, RAG, and AI agents).
- Strong understanding of scalable distributed systems, performance optimization, database technologies (e.g., PostgreSQL, Redis), and robust API development.
- Validated algorithmic thinking and a track proven history designing, 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.
Benefits
- Workday Bonus Plan
- Role-specific commission/bonus
- Annual refresh stock grants
- Comprehensive benefits
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Applied Machine Learning Scientist developing Generative AI and predictive ML solutions at TD, a major North American bank. Supporting model evaluation, deployment, monitoring, and responsible AI governance.
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