Senior Engineer, Machine Learning

Seeking an experienced Senior Machine Learning Engineer to develop and deploy ML models and solutions for Dayforce, a global HCM platform. The role involves designing, implementing, and maintaining AI components, collaborating with cross-functional teams, and providing technical leadership.

Location: United States

Salary: $128k–$228k

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.

Benefits

• Encourages personal and professional growth.
• Offers excellent time away from work programs, comprehensive wellness initiatives, and recognition through competitive pay and benefits.
• Provides opportunities for community impact through volunteer days and charity initiatives.
• Supports work-life balance and personal development.

Additional Information

• This is an ongoing opportunity; applications are reviewed periodically for future openings.
• The salary range is a guide and may vary based on experience, skills, location, and other factors.
• Candidates should be aware of and cautious about recruiting fraud, and legitimate contacts will use an @dayforce.com email address.