Staff Engineer - Machine Learning

As a Staff Machine Learning Engineer, you will serve as the critical architectural bridge between cutting-edge Data Science research and massive-scale, product-ready implementation. You will move beyond standard feature delivery to define the technical vision and infrastructure that brings sophisticated algorithms to life. Please note this is a hybrid role from Bengaluru that requires an in-office presence 3 days / week (Tue-Thu).

Responsibilities

End-to-End Pipeline Architecture: Architect, build, and manage comprehensive, highly scalable ML pipelines covering data pre-processing, model generation, automated deployment, cross-validation, and active feedback loops; ML Algorithm Implementation: Partner deeply with Data Scientists to translate complex, theoretical ML models and algorithms into high-performance, production-grade code; High-Performance Service Delivery: Design, develop, and deploy highly extensible ML API services rigorously optimized for low latency and massive scalability; Operational Intelligence & Observability: Devise and build advanced monitoring capabilities to track engineering system health and ML model performance metrics (drift, accuracy, etc.) over the long term; Strategic Innovation & Architecture: Architect solutions from scratch, leading Proof of Concept (POC) initiatives across various tech stacks; Technical Leadership & Execution: Own the full lifecycle of feature delivery autonomously, from requirement gathering with product stakeholders to final deployment, while collaborating with cross-product architects to drive platform adoption

Requirements

9+ years of progressive, highly relevant experience in software engineering and machine learning development; Proven track record of architecting, building, and productionizing complex Machine Learning solutions at enterprise scale; Deep, practical experience with modern MLOps practices; Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Mathematics, or a related quantitative field; Expert-level Object-Oriented Programming (OOP) in Python and Java; Mastery of industry-standard ML libraries and Deep Learning frameworks, including PyTorch, Keras, TensorFlow, and TFServing; Deep, advanced understanding of Data Structures, Algorithms (DSA), and complex, distributed System Design; Hands-on knowledge and proficiency with Cloud infrastructure and services (AWS highly preferred) for large-scale data processing and ML model hosting; Exceptional analytical and debugging skills with a focus on algorithmic optimization, resource efficiency, and resolving bottlenecks in distributed systems