Swiggy
Machine Learning Engineer I
SwiggyIndia1 day ago
Full-timeEngineering, Information Technology
Job Profile: Machine Learning Engineer: I

Location: Bangalore | Karnataka

Years of Experience: 1 - 3

Position Overview

You will be part of Swiggy’s Machine Learning Platform team, building the foundations that power large-scale prediction systems such as ETA, pricing, and demand forecasting.

This role combines applied modeling, data science, and engineering rigor — enabling models to be not just accurate in research but reliable, explainable, and production-ready at scale.

What qualities are we looking for?

  • Strong grasp of machine learning fundamentals — supervised learning, regularization, validation strategies, and performance metrics.
  • Working understanding of statistics and data analysis, including variance, bias, correlation, and uncertainty.
  • Proficiency in Python and numerical computing; ability to reason about algorithms and data flow.
  • Clear, reproducible coding style and comfort handling large-scale structured data.
  • Collaborative and analytical mindset with curiosity to understand why models behave the way they do.
  • Exposure to distributed data systems or ML pipelines (e.g., batch and real-time).
  • 1–4 years of experience in applied ML, data science, or software engineering (scope calibrated to level).
  • Enthusiasm for building practical, explainable, and scalable ML systems that make measurable impact.
  • Prior experience developing or deploying ML models in production environments.

What will you get to do here?

  • Contribute to the design, training, and evaluation of ML models with a focus on reproducibility, stability, and generalization.
  • Build and maintain scalable pipelines for model training, validation, and deployment.
  • Apply sound statistical reasoning to assess data quality, feature behavior, and model diagnostics.
  • Collaborate with scientists and engineers to translate analytical insights into robust ML components.
  • Support the continuous monitoring and improvement of model performance over time.
  • Champion good ML practices — controlled experiments, documentation, and interpretability.

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, disability status, or any other characteristic protected by the law.

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