AI Engineer

Overview

The AI Engineer is responsible for end-to-end development and deployment of AI‑powered data products based on machine learning over large data sets. The role involves model design, evaluation, and production rollout using standardized coding best practices. The engineer provides technical guidance to cross‑functional teams, aligns solutions with business objectives, and focuses on improving student retention and academic outcomes through actionable AI.

• Apply expertise in applied AI, model, API, and pipeline creation, and present data insights beyond numbers to understand user interactions with core products.
• Provide strategic influence with Product and Engineering teams to solve problems and identify trends and opportunities.
• Collaborate with IT managers, data stewards, and data engineers to provision AI workflows with high‑quality data, ensuring security, privacy, and scalability.
• Translate business needs into innovative yet practical AI solutions that drive measurable outcomes.
• Ensure AI output is measurable, documented, reproducible, and actively monitored for performance drift; implement continuous improvement and retraining practices.
• Manage AI resource development by gathering requirements, organizing data sources, and supporting integration of AI models into product throughout the lifecycle.
• Lead thought leadership in teams defining and evaluating strategies to improve academic outcomes using applied AI expertise.
• Support schools and school services teams to adopt actionable data for improved outcomes.
• Identify and define new opportunities to leverage AI across business units and functions in support of the company’s mission and long‑term strategy.
• Demonstrate genuine enthusiasm for education, inspiring colleagues and stakeholders to harness AI for meaningful impact on student success.

• Bachelor’s degree in Computer Science, Math, Physics, Engineering, or related quantitative field AND six (6) years of related experience, or an equivalent combination of education and experience.

• Hands‑on experience with modern ML libraries (Python frameworks such as Tensor Flow, PyTorch, scikit‑learn) and understanding of statistical principles.
• Proficiency with AWS, Azure, Docker, Kubernetes, and Terraform for scalable, secure environments.
• Design, implement, and maintain robust ML pipelines including version control, containerization, and CI/CD processes.
• Ensure model integrity and reliability by validating outputs for precise and actionable insights.
• High attention to detail and accuracy.
• Strong analytical, customer service orientation, planning, and communication skills.
• Professional integrity and confidentiality.
• Ability to manage multiple projects and meet critical deadlines independently or in a team.
• Proficiency with Microsoft Office and modern reporting platforms.
• Clear required background check.

• Master’s or Doctorate preferred.
• Additional experience with MLOps frameworks (MLflow, Kubeflow) or advanced ML techniques (NLP, recommender systems, deep learning).

Regular

The salary range is $66,379.50 to $ with potential bonus. Compensation is based on education, experience, location, and role contribution. Eligible employees may receive a robust benefits package including health benefits, retirement contributions, and paid time off.

Stride, Inc. is an equal opportunity employer. Applicants receive consideration based on merit without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status. Stride complies with all legally required affirmative action obligations and prohibits discrimination for inquiries about pay.