Lead Software Engineer - Machine Learning

Organizations everywhere struggle under the crushing costs and complexities of “solutions” that promise to simplify their lives. To create a better experience for their customers and employees. To help them grow. Software is a choice that can make or break a business. Create better or worse experiences. Propel or throttle growth. Business software has become a blocker instead of ways to get work done.

There’s another option. Freshworks. With a fresh vision for how the world works.

Freshworks Inc. builds uncomplicated service software that delivers exceptional employee and customer experiences. Our people-first approach to AI eliminates friction, helping businesses reduce complexity, lower cost-to-serve, and deliver faster, more human support through enterprise-grade yet easy-to-use CX and IT solutions. Nearly 75,000 companies, including Bridgestone, New Balance, Nucor, S&P Global, and Sony Music, trust Freshworks to power their Employee Experience (EX) and Customer Experience (CX) operations.

Fresh vision. Real impact. Come build it with us.

Responsibilities

Bridge Research and Production: Serve as the critical link translating theoretical data science research and sophisticated algorithms into product-ready, enterprise-scale implementations.; Scale to Millions: Build and deploy robust ML APIs and data pipelines engineered to handle millions of requests with high efficiency, low latency, and reliability.; Architect from Scratch: Drive organizational technical alignment by architecting high-performance ML solutions from the ground up and leading cross-functional adoption.; ML Algorithm Implementation: Collaborate with Data Scientists to translate complex models and experimental algorithms into clean, high-performance, production-grade code.; End-to-End Pipeline Architecture: Design, build, and manage comprehensive ML pipelines encompassing data pre-processing, model generation, automated deployment, cross-validation, and active feedback loops.; High-Performance Service Delivery: Develop and deploy extensible, scalable ML API services optimized for minimal latency under high traffic loads.; Operational Intelligence: Design and implement monitoring systems to track engineering efficiency and active ML model performance metrics, ensuring long-term system health.; Strategic Innovation & Collaboration: Architect technical solutions from scratch and liaise with cross-product architects and engineers to ensure organizational alignment.; Prototyping & POC Execution: Lead Proof of Concept (POC) initiatives across diverse tech stacks to identify and validate optimal infrastructure solutions for complex business challenges.; Lifecycle Ownership: Independently own the full lifecycle of feature delivery, from initial requirement gathering with product teams to final deployment and monitoring.

Requirements

Production ML Engineering: Proven capability in translating advanced mathematical models into optimized, production-ready software.; MLOps Mastery: Deep expertise in lifecycle management practices, ensuring seamless model transitions from experimental stages to live production environments.; Distributed Pipeline & API Design: Strong architecture skills in building scalable data pipelines and low-latency API microservices.; System Telemetry & Monitoring: Proficiency in establishing monitoring frameworks for tracking engineering efficiency, system health, and model performance metrics.; Technical Project Leadership: Ability to execute rapid prototyping, evaluate technical stacks, and lead cross-functional technical alignment.; Experience: 6–9 years of professional experience in software engineering and machine learning development.; Track Record: A proven history of successfully building, productionizing, and maintaining Machine Learning solutions at scale.; Education: Degree in Computer Science, Artificial Intelligence, or a related quantitative field.