Posted Apr 14, 2026
As a Senior AI/ML Engineering Manager at Curriculum Associates, you will have the opportunity to lead, mentor, and grow a team of AI/ML engineers and data scientists in a collaborative and inclusive environment. Your role will involve leading AI initiatives to deliver intelligent learning experiences across CA products and working closely with product managers, UX, research, and engineering stakeholders to define AI roadmaps. You will prioritize model functionality, technical debt, and production issues in an agile environment, ensuring timely delivery of features. Key Responsibilities:
Qualifications:
Preferred Qualifications:
Bachelor's degree in Computer Science, Engineering, Data Science, or related field
8 to 10+ years of experience in AI/ML or data-focused roles, with 3+ years managing teams
Experience with LLMs, NLP, or generative AI systems
Familiarity with large-scale data platforms or SaaS products
Knowledge of education technology and challenges in developing AI solutions for educators Join Curriculum Associates to be part of a mission-driven organization committed to improving education for all students. Embrace a work culture that values creativity, diversity, and innovation, offering competitive benefits and opportunities for professional growth. Make a meaningful impact on students and educators globally. As a Senior AI/ML Engineering Manager at Curriculum Associates, you will have the opportunity to lead, mentor, and grow a team of AI/ML engineers and data scientists in a collaborative and inclusive environment. Your role will involve leading AI initiatives to deliver intelligent learning experiences across CA products and working closely with product managers, UX, research, and engineering stakeholders to define AI roadmaps. You will prioritize model functionality, technical debt, and production issues in an agile environment, ensuring timely delivery of features. Key Responsibilities:
Lead and mentor a team of AI/ML engineers and data scientists
Collaborate with cross-functional teams to define AI roadmaps and prioritize model functionality
Drive best practices in AI development, including model quality, evaluation, explainability, and deployment
Scale AI systems for performance, reliability, and responsible use
Identify and mitigate risks related to model performance, data quality, bias, and privacy
Research, evaluate, and implement AI frameworks, platforms, and modeling approaches
Streamline AI development processes for efficiency and continuous delivery
Propose staffing plans to support annual budgeting and hiring needs
Support AI production issues, model releases, and monitoring outcomes
Qualifications:
Preferred Qualifications:
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