Applications are open for the Machine Learning Engineer position at Affirm India in Ghaziabad. You will join a working team in applied machine learning, take a defined area end to end, and see the result of your work in the hands of real users or customers.
About the role
This Machine Learning…
About Affirm India
Affirm India is hiring a Machine Learning Engineer in Ghaziabad — a full-time full-time position working in Python, PyTorch or TensorFlow and a serving stack, with an indicative CTC of 4.6 LPA–9.3 LPA and 2 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 Ghaziabad 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
2Technical or practical round based on the day-to-day work of the role
3Take-home exercise or live problem-solving discussion
4Discussion with the hiring manager on how you approach problems and work with others
5HR discussion — compensation, notice period, joining date and offer roll-out