AI Platform
/Senior leadership
Director of Engineering — AI Platform
AI Platform Leadership
Compensation
INR 50 - 80 LPA + equity.
Engagement
Full-Time
Permanent role. Full-time commitment. Primarily on-site, with limited remote flexibility.
Scope of role
Set direction within your domain. Build and mentor a team. Own outcomes at the function level.
01 — The role
Why this role exists at EduRankAI
Lead the AI platform org — training infrastructure, inference, evals, agents, observability. The systems that turn research code into production model serving. Two staff-level engineers and a growing team of mid/senior ICs report to you. You will partner closely with the research scientists. The handoff between a research notebook and a production training run is where a lot of labs lose months. You will own that handoff.
02 — The work
What you will own
- 01 Lead the AI platform team: training infra, inference, eval, agents, observability.
- 02 Own the model lifecycle from research handoff to production release.
- 03 Architect the inference fleet and serving stack (cost, latency, reliability SLOs).
- 04 Hire ML platform engineers — Staff, Senior, Mid.
- 05 Set the eval + safety release bar for every model that goes to production.
- 06 Liaise with research scientists weekly; turn hypotheses into experiment infrastructure.
- 07 Own the cost-per-token reporting that finance and the CTO depend on.
03 — The expertise
What we look for
04 — The bar
Who thrives here
- → You have led an ML platform team that trained and served at least one model at 7B+ parameters in production.
- → You have shipped at least one inference optimisation that produced a measurable cost or latency win.
- → You have hired at least two Staff or Senior ML platform engineers and retained them past 18 months.
- → You can describe a research-to-production handoff that failed and the systems change you made so it never failed the same way again.
- → You have an opinion on the right scope split between research engineering and ML platform engineering, and you can defend it.
05 — Hiring process
What to expect after you apply
- 01
Application review
Every application is read personally within five business days. We respond either way.
- 02
Take-home or live exercise
Role-specific. Time-boxed. Real problems we are actually working on, not invented puzzles.
- 03
Conversations
Deep technical and values conversations with the team you would join. No trick questions. No panel ambushes.
- 04
Offer or honest no
If yes: digital offer letter, signed in-portal, transparent terms. If no: written feedback if you want it.
Before you start
What we will collect. What it costs. What we will not do with it.
We will collect
- Name, email, phone — Account + application updates. No marketing.
- Resume / portfolio link — Human review of your work.
- Date + place of birth — Identity verification only.
- Your written responses — Selection rubric. Read by humans.
- Government ID (later) — Anti-fraud at offer / interview stage. Not at signup.
We will never
- Sell your data
- Share with third-party recruiters
- Use for advertising
- Train models on it
- Send marketing email
Our situation
EduRankAI is a small, independent organization building long-term capabilities in educational intelligence, advanced AI systems, and research infrastructure. We take no advertiser money, no donations with strings attached, and no investor pressure on hiring decisions. Applying is free, and every application is read by a human — recruitment, technical, academic and leadership teams. It buys us the right to be honest.
Ready to apply?
We read every application personally. If you are the right person for this role — regardless of pedigree, background, or where you are based — you will hear back from us within five business days.
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