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Freshworks is seeking a Staff Machine Learning Engineer to serve as the architectural bridge between data science research and production-scale ML implementation. This is a high-impact individual contributor role focused on building enterprise-grade ML systems at massive scale.
You will own the full lifecycle of ML feature delivery, from requirement gathering with product stakeholders through final deployment. Key responsibilities include:
• Architect and deploy robust ML APIs and pipelines capable of serving millions of requests with ultra-low latency and high reliability
• Partner with Data Scientists to translate complex theoretical models into high-performance, production-grade code
• Design and build highly extensible ML API services optimized for low latency and massive scalability
• Develop advanced monitoring and observability systems to track both engineering health and ML model performance metrics (drift, accuracy, etc.)
• Lead Proof of Concept initiatives across various tech stacks to validate solutions for complex business challenges
• Act as a strategic technical anchor, influencing cross-product architects and mentoring teams to ensure alignment across engineering groups
• Establish gold-standard ML Engineering practices, MLOps, and system design patterns across the organization
You will work on Freshworks' customer experience (CX) and employee experience (EX) software platform, trusted by over 72,000 companies including Bridgestone, New Balance, and Sony Music.
This is a hybrid role based in Bengaluru requiring in-office presence 3 days per week (Tuesday-Thursday).
QUALIFICATIONS & REQUIREMENTS:
• 9+ years of progressive, highly relevant experience in software engineering and machine learning development
• Proven track record of successfully architecting, building, and productionizing complex ML solutions at enterprise scale
• Deep, practical experience with modern MLOps practices and automated model deployment pipelines
• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Mathematics, or related quantitative field
• Expert-level Object-Oriented Programming (OOP) in Python and Java
• Mastery of industry-standard ML and Deep Learning frameworks: PyTorch, Keras, TensorFlow, TFServing
• Deep understanding of Data Structures, Algorithms, and distributed System Design
• Hands-on proficiency with Cloud infrastructure (AWS highly preferred) for large-scale data processing and ML hosting
• Exceptional analytical and debugging skills with focus on algorithmic optimization and bottleneck resolution in distributed systems
