About The Role What you'll be doing

You will develop and ship the predictive models behind AI Mentor — scoring learner risk in real time and powering automated interventions across email, SMS and the LMS. Practical, grounded ML with measurable impact on student success.

Key responsibilities

Your day to day

- Build, evaluate and deploy learner-risk and engagement models
- Design features from LMS, CRM and portal signals
- Stand up monitoring, evaluation and retraining pipelines
- Partner with engineering to ship models into production

Requirements What we're looking for

- 4+ years building and deploying ML in production
- Strong Python and modern ML tooling
- Solid grasp of evaluation, drift and responsible AI
- Ability to translate fuzzy goals into shippable models

Preferred Qualifications Nice to have

- Experience with education or behavioral data
- Familiarity with LLMs, RAG and guardrails
- MLOps and cloud deployment experience

Benefits What we offer Competitive salary, reviewed yearly

Fully remote with flexible schedule

Generous learning & development budget

Paid time off and wellbeing support

Top-tier equipment of your choice

Global, inclusive engineering culture

Learning opportunities

How you'll grow

- How predictive retention works at real institutional scale
- Responsible AI practice in a sensitive domain
- End-to-end ownership from model to measurable outcome

FAQ Questions, answered

Is this role fully remote?

Yes — we are remote-first and hire globally. You can work from wherever you do your best work, with overlap hours for collaboration.

What does the hiring process look like?

Application, a practical assessment, assessment review, an HR discussion, a technical interview, and a final decision — typically wrapped up in 2–3 weeks.

Do I need education-technology experience?

It helps, but it is not required.



We value strong engineering and a genuine interest in education; we will get you up to speed on the domain.

Who will I report to?

You will report to the Head of AI, and work day to day inside a small, senior pod.

DepartmentAI

LocationOn-site

- Nagercoil

Employment typeFull-time

Experience level4+ years

Working modelOn-site

Reports toHead of AI

Estimated hiring timeline

Around 2–3 weeks from application to offer.

The team A small, senior AI pod — engineers, product and QA who own outcomes together.

Hiring process

From application to offer

01

Application submission

Submit your details and resume through our application form.

02

Assessment platform

Complete a practical assessment or short course assigned to you.

03

Assessment review

Our team reviews your submission and shortlists candidates.

04

HR discussion A Conversation About You, Your Goals, And The Role. 05

Technical interview A practical session on real ed-tech problems — no whiteboard gotchas.

06

Final selection A fast, transparent offer built around how you do your best work.

Why join ZionStar

More than a job.

Career growth

Clear progression, real ownership, and the room to grow into the engineer or leader you want to be.

Mentorship

Work alongside senior ed-tech engineers who review your code and invest in your craft.

Real-world projects

Ship software used by real universities, EdTech companies and hundreds of thousands of learners.

Global exposure

Collaborate across continents on projects for organizations worldwide.

Learning opportunities A generous learning budget and time to use it — we build ed-tech, so we keep learning too.

Engineering culture

Clean architecture, tested code, small senior pods, and weekly shipping. No bureaucracy.

Ready to apply?

Tell us about yourself. After you submit, you'll complete a short assessment so we can get to know your work.

📌 Machine Learning Engineer — AI Mentor (Agasteeswaram)
🏢 KeyStone Software
📍 Agasteeswaram