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Machine Learning Talent Pool

Machine Learning Talent Pool in Surat

100+ registered early-career machine learning candidates in Surat140 with an uploaded resume.

Machine LearningDeep LearningTensorFlowPyTorchKerasScikit-learnPythonNeural NetworksMLOps

Counted live from our candidate database · updated 18 Sept 2026

Machine Learning early-career talent pool in Surat
100+
Candidates in pool
100+
With uploaded resume
15+
Hiring location
8
Graduating batches

Hiring machine learning candidates in Surat: 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.

Surat is one of the 25 hiring locations we maintain a dedicated Machine Learning pool for. The 100+ candidates in this pool are those whose home city or stated preferred work location is Surat — so this is a supply figure for hiring into Surat, 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 133SQL 92Excel 56Pandas 56Power BI 53NumPy 51MySQL 48Git 46JavaScript 44Machine Learning 39Data Analysis 33CSS 33Communication 32Java 32HTML 31React 30PostgreSQL 24Matplotlib 24

Where else this talent sits

Candidate home city or stated preferred work location.

Surat
7956%
Pune
43%
Indore
43%
Mumbai
32%
Mumbai
32%
Aurangabad
32%
Kolkata
21%
Faridabad
21%
Kolhapur
21%
Hyderabad
21%

Graduating batches

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

2029
11%
2028
64%
2027
3726%
2026
3424%
2025
2417%
2024
43%
2023
86%
2022
54%

Institutions represented

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

College
86%
University
43%
Parul University
32%
Institute of Technology
32%
Ganpat University
21%
Uka Tarsadia University
21%
GOVERNMENT ENGINEERING COLLEGE, DAHOD
11%
Sankalchand Patel College of Engineering
11%
College (GPA: 7.0)
11%
nity to gain practical industry experience
11%

Degrees in this pool

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

B.Tech / B.E. 52BCA 13MCA 9B.Tech 8B.Sc 4M.Sc 3B.E. 3BE 2

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.

Surat

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, Surat 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 Surat

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 Surat — questions answered

How many machine learning candidates are available in Surat?+

Our Machine Learning pool in Surat currently holds 141 registered early-career candidates, 140 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 Surat actually have?+

The most common skills declared by candidates in this pool right now are Python, SQL, Excel, Pandas, Power BI, NumPy, MySQL, Git, JavaScript, Machine Learning. 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 Surat?+

Candidates in this pool graduate across 2029 (1), 2028 (6), 2027 (37), 2026 (34), 2025 (24), 2024 (4), 2023 (8), 2022 (5). 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 Surat?+

Yes. Surat 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.