Sr. Engineer, Machine Learning
Dayforce · United States
- Hybrid
- Full-time
- $150,000 / year
- United States
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Job highlights
- Design and implement machine learning models and APIs.
- Develop full-stack solutions with React and Python.
- Analyze large datasets for trends and insights.
- Collaborate with cross-functional teams on AI solutions.
- Manage end-to-end ML pipelines and production deployments.
About the role
About Dayforce
Dayforce is a global human capital management (HCM) company headquartered in Toronto, Ontario, and Minneapolis, Minnesota, with operations across North America, Europe, Middle East, Africa (EMEA), and the Asia Pacific Japan (APJ) region. 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.
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.Key skills/competency
- Machine Learning
- Python
- API Development
- Cloud Platforms (AWS, Azure, GCP)
- Data Science
- Software Engineering
- Deep Learning
- NLP
- Data Engineering
- Problem Solving
Skills & topics
- Machine Learning Engineer
- AI
- Python
- TensorFlow
- PyTorch
- Scikit-learn
- AWS
- Azure
- GCP
- React
- API
- Data Science
- Software Development
- Deep Learning
- NLP
- HCM
- Remote
How to get hired
- Tailor your resume: Highlight your 6+ years of software development and 2+ years of ML/AI experience, emphasizing Python, ML frameworks, and cloud platforms.
- Showcase your full-stack skills: Detail your experience with React, Python, SQL, and API development (Flask, FastAPI) to demonstrate breadth.
- Quantify your impact: Provide specific examples of how you've designed, implemented, and deployed ML models, ideally with measurable results.
- Prepare for technical interviews: Be ready to discuss ML fundamentals, algorithms, data structures, scalable architecture, and potentially coding challenges.
- Articulate your leadership: Prepare to discuss how you've mentored junior engineers and provided technical guidance.
Technical preparation
Master Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn).,Practice building APIs with Flask or FastAPI.,Review cloud ML services (AWS, Azure, GCP).,Prepare for data structures and algorithms questions.
Behavioral questions
Describe a complex ML problem you solved.,How do you handle fast-paced, iterative environments?,Share an experience mentoring junior engineers.,How do you explain technical concepts to non-technical stakeholders?
Frequently asked questions
- What are the key responsibilities for a Senior Machine Learning Engineer at Dayforce?
- As a Senior Machine Learning Engineer at Dayforce, you will be responsible for designing, developing, and implementing machine learning models, algorithms, and API services. This includes developing full-stack solutions, analyzing large datasets, collaborating with cross-functional teams, preparing data, evaluating and optimizing models for bias and accuracy, managing end-to-end ML pipelines, and deploying models into production. You will also mentor junior engineers and stay current with AI advancements.
- What technical skills are most important for this Senior Machine Learning Engineer role at Dayforce?
- The most critical technical skills include strong programming experience in Python and machine learning frameworks like TensorFlow, PyTorch, Keras, or Scikit-learn. Experience with API development (Flask, FastAPI), frontend development (React), cloud platforms (AWS, Azure, GCP), and databases (MSSQL, NoSQL, Delta Tables) is highly valued. A strong understanding of ML fundamentals, including supervised/unsupervised learning, deep learning, NLP, and AI fairness concepts, is essential.
- Does Dayforce offer remote work for the Senior Machine Learning Engineer position?
- Yes, Dayforce is open to remote work for this Senior Machine Learning Engineer role and can hire candidates anywhere within the United States. The company emphasizes that 'Work is what you do, not where you go.'
- What kind of career growth and development opportunities are available at Dayforce?
- Dayforce encourages personal and professional growth through excellent time-away-from-work programs, comprehensive wellness initiatives, and recognition via competitive pay and benefits. They also focus on community impact and support employees in becoming the best version of themselves.
- What is Dayforce's approach to AI and machine learning innovation?
- Dayforce is actively developing innovative AI-driven products like the Dayforce AI Assistant and Dayforce Agents. The ML team operates in a fast succeed/fast fail environment, focusing on rapidly designing, implementing, and maintaining ML components, and staying current with emerging AI technologies.
- How does Dayforce ensure fairness and mitigate bias in its ML models?
- Dayforce values AI fairness and bias mitigation. The role involves identifying and analyzing potential biases in datasets, features, and model predictions, and implementing fairness and mitigation strategies. Experience with fairness-aware ML techniques is a plus.