Sr. Engineer, Machine Learning

Dayforce is a global human capital management company headquartered in Toronto and Minneapolis, offering a unified Cloud HCM platform. They are seeking a Senior Machine Learning Engineer to design and implement machine learning models and algorithms, contributing both as a hands-on engineer and a technical leader.

Responsibilities:

• Design, develop, and implement machine learning models, algorithms, and API services that meet business needs and requirements
• Develop full-stack solutions including frontend, middle-tier, and backend components using technologies such as React, Python, SQL, Delta Tables, GraphQL, and PySpark
• Apply machine learning techniques to large datasets to identify trends, patterns, and actionable insights
• Collaborate with cross-functional teams including software developers, data scientists, data engineers, and domain experts to prototype and productionize AI-driven solutions
• Prepare, clean, and preprocess large-scale datasets to ensure high data quality and suitability for training ML models
• Evaluate and optimize machine learning models for accuracy, efficiency, scalability, and bias mitigation
• Identify and analyze potential biases in datasets, features, and model predictions, implementing fairness and mitigation strategies where appropriate
• Manage end-to-end machine learning pipelines, from data preprocessing and feature engineering through training, deployment, monitoring, and continuous improvement
• Deploy and integrate machine learning models into production environments and implement monitoring systems for usage, performance, and feedback collection
• Develop and maintain ML software systems, reusable libraries, testing frameworks, and automated test suites
• Participate in research and development of emerging machine learning and AI technologies
• Mentor junior engineers and contribute technical leadership within the team
• Stay current with advancements in machine learning, AI technologies, cloud infrastructure, and software engineering best practices

Requirements:

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Statistics, or a related field. Equivalent practical experience will also be considered
• 6+ years of overall software development experience
• 2+ years of experience in machine learning and AI software development
• Strong programming experience in Python and machine learning frameworks such as TensorFlow, PyTorch, Keras, or Scikit-learn
• Experience building APIs and backend services using frameworks such as Flask or FastAPI
• Experience with frontend development using React
• Strong understanding of supervised and unsupervised learning, deep learning, reinforcement learning, NLP, ensemble methods, and ML fundamentals
• Familiarity with AI fairness concepts and bias detection/mitigation techniques
• Experience with cloud platforms such as AWS, Azure, or GCP and their machine learning services
• Experience working with relational and non-relational databases, including MSSQL, NoSQL, Delta Tables, and related technologies
• Strong understanding of data structures, algorithms, design patterns, and scalable software architecture
• Experience with CI/CD pipelines, Docker containers, and cloud-based ML deployment workflows
• Strong analytical, problem-solving, and critical-thinking skills
• Excellent communication and collaboration skills, with the ability to explain complex technical concepts to technical and non-technical stakeholders
• Experience with data visualization, feature engineering, and data manipulation techniques
• Practical experience detecting and mitigating model bias using fairness-aware ML techniques
• Experience building and deploying ML-powered products in production environments
• Experience with AWS cloud infrastructure and tooling
• Contributions to open-source ML projects or a portfolio of previous ML work