Machine Learning Engineer (Associate/Senior)

About the Company

Quantiphi is an award-winning company that builds data science and machine learning software and services. Its focus is on helping businesses turn machine learning and AI into measurable commercial value. The organization was founded on the idea that these technologies can significantly improve customer experience and operating efficiency. Quantiphi is one of Google’s five global launch partners for machine learning and one of the three global launch partners for Google Cloud Contact Center AI. Its approach blends advanced ML research with strong cloud and data engineering practices to deliver impact quickly. The company’s guiding belief is: solving what matters.

Role Overview

The opening is for a Machine Learning Engineer at the Associate Architect/Senior level, with 3 to 9 years of relevant experience. The position is based across Mumbai, Bangalore, and Trivandrum.

Key Responsibilities

• Build complete AI/ML solutions for production-grade use cases, going beyond proof-of-concept work.
• Work with large datasets to uncover useful business insights.
• Present analytical findings clearly to clients and internal teams.
• Develop, improve, refine, and support existing machine learning models to strengthen overall solution performance.
• Collaborate effectively with stakeholders and manage team interactions smoothly.
• Partner with external stakeholders to define ML requirements and shape solution enhancements.

Required Skills and Experience

• Practical coding experience with strong command over Python and SQL.
• Experience using PySpark.
• Strong analytical ability with close attention to detail.
• Working knowledge of ML methods such as logistic regression, clustering, decision trees, XGBoost, LightGBM, statistical modeling, and predictive analytics.
• Experience with time-series forecasting techniques including ARIMA, SARIMA, and Prophet.
• Exposure to deep learning methods and artificial neural networks.
• Familiarity with Databricks and Azure-based environments.
• Background in building scalable, interactive, and high-performance ML systems.
• Hands-on experience taking models into production.
• Exposure to post-deployment support and MLOps is an added advantage.
• Prior work in the Retail or CPG domain is also a plus.

Eligibility

Candidates holding B.Sc., B.C.A., or B.Tech/B.E. degrees in any specialization may apply.

Additional Information

This role is intended for full-scale machine learning delivery in real-world business settings, with an emphasis on stakeholder coordination, model productionization, and continuous enhancement of deployed solutions.