ML Engineer — Personalization

About this ML Engineer role at Unacademy

Unacademy, India's largest learning platform, is hiring ML Engineers to build personalization and recommendation systems that shape how millions of students discover courses. This is a mid-level opportunity in Bengaluru for engineers who want to move from learning models to deploying them at scale — directly impacting user experience for India's edtech learners.

What you'll do

• Design and optimize recommendation systems using retrieval and ranking techniques to personalize course discovery for Unacademy's user base
• Build and train machine learning models in Python and PyTorch to predict user preferences and engagement patterns
• Run A/B tests to measure the impact of recommendation changes and validate model improvements in production
• Collaborate with product and data teams to translate business goals into ML systems that drive user retention and learning outcomes
• Maintain and iterate on ranking algorithms that balance relevance, diversity, and business metrics at scale

Who should apply

You should have 3+ years of hands-on experience building recommendation systems or working on retrieval and ranking problems. Mid-level ML engineers with a strong foundation in Python, PyTorch, and A/B testing are the right fit. You don't need edtech experience—strong fundamentals in recsys are what matters. If you've shipped personalization features or worked on ranking in production, you're competitive.

Salary & offer in context

This role offers ₹20–40 LPA (₹1,66,667–₹3,33,333 per month depending on experience and negotiation). For a mid-level ML Engineer in India, this sits in the upper-middle range—comparable to what mature startups and product companies pay for personalization expertise. ML Engineer salaries in India typically range ₹15–50 LPA, so this offer reflects both the startup's scale and the specialized nature of recommendation systems work.

Path to apply

This is a direct online application through Unacademy's careers portal—no exam or preliminary screening hoop. Apply by 4 June 2026 to stay in the active review window. Unacademy typically fast-tracks candidates with strong recsys portfolios, so highlight any published work, Kaggle competitions, or production systems you've built.