GoMeasure Platform runs GoMeasure Campus — a talent network for final-year students and new graduates, where what you can do is measured from real work rather than claimed on a CV.
We’re looking for Graduate AI/ML Engineers to join this network ahead of the placement cycle. Train, fine-tune and deploy models, and evaluate them against something more rigorous than a demo.
You’ll take one qualification test covering ml fundamentals, python, evaluation, build a verified profile, and go to the employers hiring into this track — typically ₹6–16 LPA at entry level.
Role summary
Train, fine-tune and deploy models, and evaluate them against something more rigorous than a demo.
What you will do
In the first six months
- Train and fine-tune models, and spend far more time on the data than on the model
- Build the evaluation that tells you whether a change helped, rather than trusting that it looks better
- Get something into production and discover what that actually costs
- Read papers and work out which parts apply to your problem and which do not
By twelve to eighteen months
- Own a model in production and its behaviour as the data shifts underneath it
- Make the call on whether a problem needs machine learning at all
- Design evaluation for a system that has no single right answer
Required skills
ML fundamentalsHow models actually learn, what overfitting looks like, and why a validation split matters. Deep-dive rounds probe this hard, and frameworks do not cover for a gap here.
PythonFluent, not just familiar. Screened alongside data structures in most loops.
Data structures & algorithmsStill a gate. The coding round is typically a medium-difficulty problem with an ML twist rather than pure algorithms.
EvaluationDeciding what 'better' means for your system and measuring it honestly. The 2026 version of this question is increasingly 'how would you evaluate a chatbot?'
Production reasoningLatency, cost, monitoring and what happens when the model degrades. Deep rounds ask production scenarios, not only theory.
Disposition & traits
Skills describe what someone can do when they try hardest. Disposition describes what they typically do — and over a first year, that second question predicts as much as the first. For this track the dispositions that matter most are:
- Scepticism
- Openness to experience
- Judgement under uncertainty
How to read these. Higher is not automatically better — a disposition that helps in one role works against another. These are not a pass mark, not trainable in the way a skill is, and never reported on their own.
What the hiring bar looks like
Compiled by GoMeasure from publicly available accounts, October 2026.
Product companies & startupsA recruiter screen, a technical screen on a project you built, then a long deep round — often two to four hours — covering live coding, ML fundamentals and production scenarios, then a hiring-manager round.
IT servicesThe large services employers now run dedicated AI/ML screening within their premium tracks, rather than allocating AI work after joining.
GCCsA product-style loop with stronger emphasis on fundamentals and system design.
Eligibility — who actually gets to apply
The academic bar can be steep — one 2026 fresher posting required 80% across 10th, 12th and degree with no backlogs ever, not merely none active. What moves the needle more than marks is deployed work: two projects at a public URL a stranger can open, each with a stated problem, a measured result and an honest note on what it does not handle. That is also what a technical screen is built around.
Eligibility is set per drive and your placement cell’s notice is what actually applies on your campus. One trap worth knowing: a 6.0 CGPA is not always 60%. Where a university converts with (CGPA − 0.75) × 10, a 6.0 is 52.5% — below most employers’ floor. Check which formula yours uses before assuming you qualify.
And on the package: CTC is not take-home. A ₹4 LPA offer lands nearer ₹28,000–32,000 a month once provident fund, gratuity and tax come out, and offers with a large variable or joining-bonus component differ more again. Compare offers on fixed monthly pay, not on the headline. On-campus mass recruiters rarely move off a standard package; startups, GCCs and mid-size firms hiring off-campus often have some room.
Who should apply
Graduates whose degree and interests line up with the work above. Eligibility aside, employers in this track screen on demonstrated capability more than on which campus you attended.
This role is probably not for you if you want to work on products rather than systems, or you find evaluation and measurement tedious. Most of this job is establishing whether something actually works.
Evaluation notice
Results are shared with the student and, with consent, with employers hiring into this track. Scores carry the evidence and the assessment date. Practice and assessed sessions are clearly distinguished before either begins.