AI Engineer

Applies expertise in applied AI, model, API, and pipeline creation, as well as the presentation of data to see beyond the numbers and understand how our users interact with our core products; Provide strategic influence with Product and Engineering teams to solve problems and identify trends and opportunities; Collaborates with IT managers, data stewards, and data engineers to ensure that AI workflows are efficiently provisioned with high-quality data and follow best practices in security, privacy, and scalability; Informs, influences, and supports product direction by translating business needs into innovative yet practical AI solutions that drive measurable outcomes; Ensures that AI output is measurable, documented, reproducible, and actively monitored for performance drift. Implements practices for continuous improvement and retraining as needed; Manages the development of AI resources by gathering requirements, organizing data sources, and supporting the integration of AI models into product throughout the product lifecycle; Holds a key thought leadership role on teams responsible for defining and evaluating strategies to improve academic outcomes, leveraging applied AI expertise to inform decisions; Ensures that Stride's AI capabilities support schools and school services teams, facilitating adoption and use of actionable data to deliver improved outcomes; Identifies and defines new opportunities to leverage AI across different business units and functions in support of Stride's mission, vision, and long-term strategy; Demonstrates genuine enthusiasm for education and the Stride experience, 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' related experience; OR Equivalent combination of education and experience Hands-on experience with modern ML libraries (e.g., Python-based frameworks such as TensorFlow, PyTorch, scikit-learn) and understanding of statistical principles. Proficiency with AWS, Azure, Docker, Kubernetes, and Terraform to build scalable, secure, and high-performing environments. Ability to design, implement, and maintain robust ML pipelines, including version control, containerization (Docker, Kubernetes), and CI/CD processes. Ensures model integrity and reliability, validating outputs to deliver precise and actionable insights. High attention to detail and high level of accuracy. Strong analytical skills. Strong customer service orientation. Professional integrity necessary to maintain confidentiality. Strong planning skills and ability to manage multiple projects simultaneously. Excellent verbal, and written communication skills. Ability to complete assigned duties within critical deadlines. Ability to work independently and in a team environment. Proficient with Microsoft Office (Word, Excel, PowerPoint, and Outlook). Proficiency with modern reporting platforms and tools. Ability to grasp complex platform concepts and business models, in a digital context. Ability to clear required background check Master's/Doctorate preferred Additional experience with MLOps frameworks (e.g., MLflow, Kubeflow) or advanced ML techniques (e.g., NLP, recommender systems, deep learning) This is a home-based position To view full details and how to apply, please login or create a Job Seeker account