Director - Academics (AI/ML)

About the Role:

We are looking for a Director of Academics to lead the delivery of AI/ML learning products at scale. This is a strategic leadership role where you will be responsible for program planning, content operations, quality assurance, and partner integrations across our Data Science, Machine Learning, and Generative AI programs. This role combines academic depth with industry scale, reaching 3,000+ working professionals annually through our university partnerships. The right candidate will turn the latest GenAI and LLM research into practical educational programs that help learners succeed, meet university standards, and reduce operational challenges. This role requires a unique blend of technical AI/ML expertise, academic experience, and product thinking.

Program Portfolio:

You will serve as the Academic Lead for a range of programs, including:

MSc/M.Tech programs in Data Science, Machine Learning, and Computer Science (AI).

Professional certificates in Data Science, Machine Learning, Cloud Computing, and GenAI.

Specialized programs in AI, Emerging Tech, and Design.

Data Science and ML Bootcamps.

Other programs within the Data and Tech vertical, as needed.

Key Responsibilities

1. Academic Strategy and Program Design

Ensure programs meet university academic standards across all Data and Tech programs

Design program roadmaps working closely with Delivery, Content, Product, Technology, and SME teams

Work with university partners to develop hands-on curricula

Ensure alignment with university-defined learning outcomes and relevant skills frameworks

2. Quality Assurance and Governance

Implement and operationalize university-approved rubrics, audits, and grader calibration systems Use scorecard frameworks (Red/Amber/Green) to track grading quality

Support grader recruitment and training in line with university guidelines

Create standard processes for live delivery and assessments to ensure reliable quality

3. University Partnership and Compliance

Act as the main academic contact for university partners

Hold regular academic review meetings and track compliance

Make sure assessment practices follow university rules and policies

Coordinate internal quality checks to support university moderation processes

Create action plans and give regular updates to university stakeholders

4. Team Leadership and SME Management

Lead a team of 10 or more content and subject matter experts

Manage hiring, onboarding, and performance of thesis supervisors and graders

Develop operational guides for thesis supervisors aligned with university requirements

Run weekly or bi-weekly training sessions to answer questions and improve quality

Set hiring criteria and conduct interviews for SME recruitment

5. Teaching and Research

Take part in teaching sessions, live workshops, and thesis supervision

Facilitate learner support sessions on thesis writing and research methods

Help learners turn thesis work into real projects they can show employers

Lead practitioner workshops and capstone projects for skill building

Publish research and present at conferences with support from upGrad's industry and university partnerships

6. Content and Delivery Improvement

Review all program materials (videos, text, case studies, resources) for quality and relevance

Run internal reviews and check live session quality through audits

Work with the content and product teams to build AI-powered education tools

Create playbooks, checklists, and guides that help learners get value faster

7. Learner Success

Hold monthly group discussions and cohort meetings to track learner progress

Collect and act on feedback to make the learning experience better

Create consistent learning experiences across all cohorts

Help with learner questions and join marketing or counselling sessions when needed

Required Qualifications

Education

PhD in Applied Mathematics, Computer Science, Data Science, Machine Learning, or a related field (Required)

Prior teaching experience at universities or colleges is highly valued

Extra certifications in Adult Learning, Instructional Design, or Education are a plus

Experience

8 or more years of combined experience in AI/ML, data science, or higher education

3 or more years in academic leadership, teaching, program management, or EdTech product roles Proven experience designing and delivering AI/ML programs

Experience working with university partners and meeting academic compliance requirements

Published research in good journals (Q1/Q2 in SCI) is preferred