AI and ML Recruitment Agency in Pune
Most AI hiring in Pune serves businesses that make, move or run things: industrial, enterprise and engineering-led companies. Talhive runs dedicated search for the data and applied ML people who put models into those operations.
- Assessed on production evidence
- Shortlist of five profiles at most
- 90-day replacement guarantee
The quality of a search is determined early. Start with the role, the context, and what a strong hire looks like at 12 months.
Your details are held in strict confidence and are not shared with third parties.
Received.
A senior team member will review your enquiry and respond directly.
Applied machine learning where data meets industry
Pune's engineering and manufacturing heritage shapes its AI work. The question is rarely how to build a consumer chatbot. It is how to use data from machines, software and operations to make a plant, product or enterprise system work better.
That calls for people who join messy data to real processes and keep models running after launch. Talhive runs AI and ML search as dedicated work, with milestone-based fees agreed before work starts. Our guide to senior AI engineers in India sets out the approach.
Data and ML roles an industrial employer needs
Matched to the business problem, not to a fashionable title.
Data engineers
People who build the pipelines, storage and quality checks that models depend on.
Applied ML engineers
Engineers who take a model from experiment to a service others rely on, including monitoring.
Heads of data and ML
Leaders who set priorities, build the team and explain results to the business. For a chief-level appointment, see executive search in Pune.
Data foundations before model builders?
A question worth answering before any search begins.
When data comes first.
If data sits in scattered systems without owners, a model builder will spend their time cleaning, not modelling. A data engineer is then the better first hire.
When ML can lead.
If pipelines are reliable and the business question is clear, an applied ML engineer can show value sooner. Our note on the AI, ML and data science roles helps you choose.
Ask for a view.
We give an honest read on which hire your situation needs first, even if it is not the one you came to brief.
Research profile or production profile
Both are valuable. They solve different problems.
The research profile
Strong on methods, papers and model design. It suits novel problems, but not every enterprise brief needs it.
The production profile
Has run models on live data, handled drift and answered for failures. For most enterprise and industrial roles, this is the one.
Match the profile to the brief
Decide which you need before outreach, and write the brief to attract it. Our piece on why CV screening fails senior AI hires explains why the signal is hard to read.
Judging ML work by what ran in production
Evidence, not keywords or titles, at every stage.
- Stage one01
Define the problem.
- What the hire must make work in the first year
- State of the data and the systems around it
- Research or production profile
- Stage two02
Map quietly.
- Industrial, enterprise and product employers considered
- Approaches written around the work
- Confidentiality agreed before outreach
- Stage three03
Assess on production evidence.
- What each person shipped, ran and fixed
- A written synopsis for every profile
- An honest view of fit and risk
- Stage four04
Close and protect.
- Offer strategy and counter-offer planning
- Notice-period tracking until the start date
- 90-day replacement guarantee on the placement
Checks to make before commissioning an ML search
Most can be settled in one internal meeting.
A vague AI title
If the role could mean analyst, engineer or researcher, the search returns all three. Name the work.
Unclear data readiness
A strong hire cannot compensate for data nobody owns. Know where it lives and who is responsible.
No path to production
Ask who will deploy and maintain what the hire builds. Otherwise the first model may never leave a notebook.
Hiring machine learning talent: your questions
Plain answers to the questions we hear most often about this search.
Share the problem, we will scope the search
Describe the business problem, the state of your data and the team around the hire. A founder responds to every brief.
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