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Machine Learning Talent Pool

Machine Learning Talent Pool in Gurgaon

7 registered early-career machine learning candidates in Gurgaon7 with an uploaded resume.

Machine LearningDeep LearningTensorFlowPyTorchKerasScikit-learnPythonNeural NetworksMLOps

Counted live from our candidate database · updated 4 Aug 2026

Machine Learning early-career talent pool in Gurgaon
7
Candidates in pool
7
With uploaded resume
5+
Hiring location
3
Graduating batches

Hiring machine learning candidates in Gurgaon: what you're actually working with

Machine learning candidates overlap heavily with data science, but the hiring bar is different: ML roles need people who can put a model into production, not just train one. Candidates with any deployment or MLOps exposure are a small fraction of the pool and should be prioritised in screening.

Gurgaon is one of the 25 hiring locations we maintain a dedicated Machine Learning pool for. The 7 candidates in this pool are those whose home city or stated preferred work location is Gurgaon — so this is a supply figure for hiring into Gurgaon, not a national number filtered down for display.

Live pool data

What this pool looks like right now

Read from candidate profiles, not from a brochure. Everything below refreshes every six hours.

Skills present in this pool

Declared by candidates on their own profiles.

Python 7SQL 6Power BI 5Excel 4Big Data 2Node.js 2C++ 2Data Analysis 2Pandas 2Express.js 2NumPy 2MongoDB 2TypeScript 2JavaScript (ES6+) 1Communication 1PostgreSQL 1Postman. 1Backend & APIs/Databases: Node.js 1

Where else this talent sits

Candidate home city or stated preferred work location.

Gurugram
229%
Delhi
229%
Faridabad
114%
Gurgaon
114%
gurgaon
114%

Graduating batches

Plan a 2027 cohort in 2026 — filter by batch in the Talent Desk.

2027
343%
2026
343%
2025
114%

Institutions represented

Colleges with the most candidates in this pool, as entered by candidates.

Thapar Institute of Engineering and Technology Patiala
114%
Dr. Akhilesh Das Gupta Institute of Professional Studies
114%
Delhi Technical Campus
114%
Dronacharya College Of Engineering
114%
University
114%
UIET MAHARSHI DAYANAND UNIVERSITY, ROHTAK
114%
Chandigarh uniersity
114%

Degrees in this pool

We do not filter on degree unless your requirement asks us to.

B.Tech / B.E. 3B.Tech 1B.Tech 1BPES 1BE 1

Roles employers hire into

Typical early-career titles for this pool.

  • Machine Learning Intern
  • ML Engineer Trainee
  • Deep Learning Intern
  • MLOps Intern
  • Graduate ML Engineer
MyInternships Talent Desk

Tell us your hiring requirement.We'll tell you who's available.

Don't post a job and wait. State what you need and see the live size and shape of the matching talent pool — before you commit to a hiring plan.

Gurgaon

How to screen this pool

Volume is rarely the constraint in machine learning hiring — signal is. These are the screens that separate a hireable candidate from a well-formatted résumé.

  • Has anything they built ever served a real request?
  • Comfort with versioning, reproducibility and monitoring
  • Ability to debug a model that degrades in production
  • Solid Python engineering, not only notebooks

How the process runs

Four steps from requirement to shortlist. You never write a job description.

  1. 1

    State the requirement

    Role, volume, Gurgaon and graduating batch — in plain English.

  2. 2

    See the matching pool

    A live count plus the city, batch and college split of who matches.

  3. 3

    Request the shortlist

    Verified profiles with resumes and contact details, ranked by fit score.

  4. 4

    Run your process

    Interview and close. Next cycle, change the batch year and repeat.

Candidate availability, honestly

We derive availability from real platform activity rather than a self-declared field. Active in the last 14 days reads as actively looking, within 45 days as open to offers, and beyond that as passive. Shortlists are weighted towards candidates who will actually reply to you.

Hire machine learning candidates in Gurgaon

Tell us the volume, the cities and the graduating batch. Our talent desk comes back with a matched shortlist — verified profiles, resumes and contact details.

  • Machine Learning Intern through to Graduate ML Engineer
  • Bulk and multi-city requirements as a single brief
  • Batch-aware pipelines for 2026, 2027 and 2028 cohorts
  • Campus & early-careers requirements answered first

Request Machine Learning candidates

Matched against this pool, ranked by fit.

Graduation batches

Your details stay with our talent desk. No candidate data is shared without consent.

Machine Learning hiring in Gurgaon — questions answered

How many machine learning candidates are available in Gurgaon?+

Our Machine Learning pool in Gurgaon currently holds 7 registered early-career candidates, 7 of them with an uploaded resume. That figure is a live count from our candidate database, refreshed every six hours — not an estimate. Use the Talent Desk above to narrow it by graduating batch, specific skills or a tighter location and see the matching number instantly.

Which skills do machine learning candidates in Gurgaon actually have?+

The most common skills declared by candidates in this pool right now are Python, SQL, Power BI, Excel, Big Data, Node.js, C++, Data Analysis, Pandas, Express.js. These are read from real candidate profiles, so the list shifts as the pool changes. The skills we match a Machine Learning requirement against are Machine Learning, Deep Learning, TensorFlow, PyTorch, Keras, Scikit-learn, Python, Neural Networks and related technologies.

Which graduating batches can I hire in Gurgaon?+

Candidates in this pool graduate across 2027 (3), 2026 (3), 2025 (1). Campus and university-relations teams typically build a pipeline one to two batches ahead — filter by batch in the Talent Desk to see exactly what is available for your target cycle.

How should we screen machine learning candidates?+

Has anything they built ever served a real request?. Comfort with versioning, reproducibility and monitoring. Ability to debug a model that degrades in production. Solid Python engineering, not only notebooks. Machine learning candidates overlap heavily with data science, but the hiring bar is different: ML roles need people who can put a model into production, not just train one. Candidates with any deployment or MLOps exposure are a small fraction of the pool and should be prioritised in screening.

Which roles do employers hire from this pool?+

Most commonly Machine Learning Intern, ML Engineer Trainee, Deep Learning Intern, MLOps Intern, Graduate ML Engineer. Candidates typically come from B.Tech CSE/AI-ML, M.Tech, M.Sc, MCA backgrounds, though we do not filter on degree unless your requirement asks us to.

Do I have to post a job to hire from this pool?+

No. This is a talent-access product, not a job board. You describe the requirement — role, volume, location and batch — and our talent desk returns matched candidate profiles with resumes and contact details. Job posting exists separately on MyInternships and is unaffected by this.

How is candidate availability determined?+

From real activity on the platform, not a self-declared status. Candidates who have been active in the last two weeks show as "actively looking", up to 45 days as "open to offers", and beyond that as passive. That means the availability signal on a shortlist reflects who will actually respond to you.

Can you also source machine learning talent outside Gurgaon?+

Yes. Gurgaon is one of 25 cities we maintain dedicated Machine Learning pools for, and we source pan-India including tier-2 and tier-3 locations. Multi-city requirements are handled as a single brief, and the Talent Desk shows you the city-by-city split before you commit headcount.