Senior Machine Learning Engineer — MLOps & Feature Store Architecture
Location: Bengaluru / Hyderabad / NCR (Hybrid / Remote Flexibility)
Employment Type: Full time
Department: Core ML Infrastructure & MLOps
Experience Range: 3–6 Years

About the Company & Engineering Culture

Building high-performing machine learning models is only half the battle; reliably training, versioning, monitoring, and serving them at production scale is where true engineering excellence lies. As a high-growth AI and SaaS enterprise, our platform orchestrates complex machine learning pipelines that handle massive throughput, real-time feature transformations, and continuous model inference across multi-tenant settings.

Our MLOps engineering culture focuses on immutable artifact versioning, zero-downtime model deployments, automated data drift monitoring, and optimized GPU/CPU infrastructure performance. We bridge the gap between data scientists and production software engineers. If you are passionate about building robust, scalable infrastructure that powers enterprise AI at scale,



this is your arena.

Position Overview

We are looking for a hands-on, detail-oriented Senior Machine Learning Engineer (MLOps) to design, build, and scale our enterprise MLOps platforms, feature stores, and automated model deployment pipelines. In this role, you will own the technical execution of taking machine learning models from experimental Jupyter notebooks into robust, low-latency, monitored production microservices.

You will work closely with applied ML scientists, data engineers, and cloud infrastructure architects to ensure our AI systems maintain high availability, reproducibility, and optimal inference performance.

Key Responsibilities & Technical Ownership1. MLOps Pipeline Automation & CI/CD
ML Pipelines: Design, build, and maintain end-to-end ML CI/CD pipelines for automated data ingestion, feature extraction, model training, and containerized deployment using tools like MLfl

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