Freshworks: Staff Engineer - Machine Learning — Bengaluru, KA, India

About Freshworks

Freshworks develops cloud-based software for customer and employee experiences. Its product range includes customer support, sales and marketing automation, chat and IT service management. The employer names Freshdesk, Freshsales, Freshmarketer, Freshservice and Freshchat, supported by shared platform services. These applications address different operational needs, from managing customer conversations and sales activity to helping employees obtain IT services. The business emphasises software designed for end users and straightforward implementation.

The position and its setting

Freshworks lists Staff Engineer - Machine Learning in Bengaluru, KA, India, under reference P-1001848_1. The details below separate the work described by the employer from essential conditions, preferred experience and practical preparation advice.

• Employment type: Full-time
• Employer listing date: 15 October 2026
• Brands: Freshworks

Responsibilities and work described

• 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
• Move beyond standard feature delivery to define the technical vision and infrastructure that brings sophisticated algorithms to life
• Your work will directly result in:
• Massive Scale & Reliability: Architecting and deploying robust ML APIs and pipelines capable of serving millions of requests with ultra-low latency and unwavering reliability
• Engineering Excellence: Setting the gold standard for ML Engineering practices, MLOps, and system design across the organization
• Accelerated AI Innovation: Transforming theoretical models into high-performance, production-grade systems, directly shrinking the time-to-market for complex ML business solutions
• Cross-Organizational Multiplier: Acting as a strategic technical anchor, influencing cross-product architects, leading POCs, and mentoring teams to ensure tight technical alignment across all engineering groups
• 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 both 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 to validate optimal solutions for complex business challenges
• 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

Essential requirements and candidate background

• 9+ years of progressive, highly relevant experience in software engineering and machine learning development
• Production Excellence: A proven, demonstrable track record of successfully architecting, building, and productionizing complex Machine Learning solutions at an enterprise scale
• MLOps Mastery: Deep, practical experience with modern MLOps practices, ensuring seamless, automated, and secure model transitions from development and training into production environments
• Education: A Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Mathematics, or a related quantitative field
• Core Programming: Expert-level Object-Oriented Programming (OOP) expertise in Python and Java
• ML & Deep Learning Frameworks: Mastery of industry-standard ML libraries and Deep Learning frameworks, including PyTorch, Keras, TensorFlow, and TFServing
• Foundational Engineering: Deep, advanced understanding of Data Structures, Algorithms (DSA), and complex, distributed System Design
• Analytical Problem Solving: analytical and debugging skills with a relentless focus on algorithmic optimization, resource efficiency, and resolving bottlenecks in distributed systems

Preferred experience and additional strengths

• Cloud & Infrastructure: Hands-on knowledge and proficiency with Cloud infrastructure and services (AWS highly preferred) for large-scale data processing and ML model hosting

Location, schedule and contract conditions

• Please note this is a hybrid role from Bengaluru that requires an in-office presence 3 days / week (Tue-Thu)
• Work arrangement: On-site
• Advertised location: Bengaluru, KA, India

Pay and application dates

A verified salary figure is not established in this article. An online estimate for another Staff Engineer - Machine Learning vacancy is not an offer for reference P-1001848_1; use the employer’s own pay disclosure and recruitment communication.

A closing date is not confirmed in this article. Check the current employer page before submitting: an undated posting can change or be withdrawn.

How to apply to Freshworks

Applications follow the official employer page linked below.

Open the official Freshworks posting below and match the title and reference P-1001848_1.

Compare your qualifications and experience with the essential conditions for the Bengaluru, KA, India position, then read the preferred criteria separately.

Prepare an accurate CV and the supporting items requested in that employer’s application. Provide only information and documents you are authorised to share.

Use the employer’s application option, complete the required fields and review the submission. Retain the acknowledgement when one is provided. Job Alerts World does not receive the application.

Practical preparation: Python

Python work is easier to assess through a concrete example than a list of libraries. Explain the problem, the input data, the parts you implemented and how you checked the output. Include a repository or a short technical note when you can share it.

Relevant skills

• Python
• Java
• AWS
• APIs
• AI/ML
• machine learning
• AI
• stakeholder management
• training