47Billion is recruiting a Machine Learning Engineer for its Nagpur team. The role suits someone early in their career who wants depth in applied machine learning rather than a rotation through everything at once.
About the role
This Machine Learning Engineer position is about training models and —…
About 47Billion
47Billion is hiring a Machine Learning Engineer in Nagpur — a full-time full-time position working in Python, PyTorch or TensorFlow and a serving stack, with an indicative CTC of 4.8 LPA–9.5 LPA and 3 openings.
PythonScikit-learnPyTorch or TensorFlowFeature EngineeringModel EvaluationSQLModel DeploymentExperiment TrackingStatisticsGit
Who Can Apply
B.E./B.Tech, BCA/MCA, B.Sc/M.Sc (Statistics / Mathematics) or MBA (Analytics) graduates with 0–2 years of relevant experience, based in Nagpur or willing to relocate. You should be comfortable with Python, Scikit-learn, PyTorch or TensorFlow, Candidates from any recognised university are welcome, and career-changers with demonstrable skills are read on the same terms as fresh graduates. Freshers and final-year students awaiting results are welcome to apply — the selection process is designed to test how you think, not how much you have already memorised.
Perks
Support for internal mobility across teamsFixed monthly salary, paid on timeStructured onboarding with a named mentor for the first 90 daysHealth insurance cover for you (and family cover on confirmation)Learning and certification budgetPaid leave, casual leave and public holidaysFlexible working hours around core collaboration timeModern hardware and the tool licences your role needs
Interview & Selection Process
5 rounds — typical selection flow for this role:
1Resume screening and profile shortlisting by the talent acquisition team
2Team fit conversation with two or three future colleagues
3Final discussion covering role expectations, compensation and start date
4Application screening (CV and, where relevant, a portfolio or code sample)
5HR discussion — compensation, notice period, joining date and offer roll-out