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Sr. Engineer, Machine LearningDayforce • United States
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Sr. Engineer, Machine Learning

Dayforce
  • US
    United States
  • US
    United States
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Über

Senior Machine Learning Engineer
Our award-winning Cloud HCM platform offers a unified solution database and continuous calculation engine, driving efficiency, productivity and compliance for the global workforce. Our brand promise - Makes Work Life Better™ - reflects our commitment to employees, customers, partners and communities globally. Location: Work is what you do, not where you go. For this role, we are open to remote work and can hire anywhere in the United States. About the Opportunity
We are seeking an experienced and talented Senior Machine Learning Engineer to join our ML team. As a Senior Machine Learning Engineer, you will work on delivering ML components for innovative products such as Dayforce AI Assistant and Dayforce Agents. This role involves rapidly designing, implementing, evaluating, and maintaining machine learning models, algorithms, APIs, and software systems in a fast succeed/fast fail environment. You will contribute both as a hands-on engineer and as a technical leader, helping guide solutions from prototype through production while ensuring performance, scalability, reliability, and maintainability. What You'll Get to Do
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. Skills and Experiences We Value
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. What Would Make You Really Stand Out
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. If you are highly motivated, thrive in fast-paced environments, and enjoy rapidly applying new and existing AI techniques to solve evolving problems, this role may be a great fit for you. You will work across both generative AI applications using unstructured data and AI solutions leveraging structured enterprise data. What's in It for You
Dayforce is fueled by the diversity of our talented employees. We are an equal opportunity employer and consider and embrace ALL individuals and what makes them unique. We believe our employees should be happy and healthy, with peace of mind and a sense of fulfillment. We encourage individuals to apply based on their passions. Dayforce encourages personal and professional growth. We offer excellent time away from work programs, comprehensive wellness initiatives and recognition through competitive pay and benefits. With a commitment to community impact, including volunteer days and our charity, Dayforce Cares we provide opportunities for you to thrive both in your career and personal life. Our focus is not just on your job but on supporting you to be the best version of yourself. About the Salary Ranges Please note that the salary range mentioned in this job description should serve simply as a guide. The final compensation offered may vary based on a variety of factors, including bonuses and/or incentives, or a candidate's experience, skills, budget and location. Our company is committed to providing a fair, equitable, and competitive package that reflects the value an individual brings to the organization. Fraudulent Recruiting Beware of fraudulent recruiting. Legitimate Dayforce contacts will use an @dayforce.com email address. We do not request money, checks, equipment orders, or sensitive personal data during the recruitment process. If you have been asked for any of the above, or believe you have been contacted by someone posing as a Dayforce employee, please refer to our fraudulent recruiting statement found here: https://www.dayforce.com/be-aware-of-recruiting-fraud Dayforce actively monitors all job applications to ensure authenticity. Submissions determined to be fraudulent or misleading will be declined from the recruitment process.
  • United States

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  • English
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