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AI/ML Engineer - Omnichannel Communication Platform

eDAS
5 - 10 Years
Gurgaon/Gurugram

Posted on: 25/04/2026

Job Description

Description :

Role : AI/ML- Engineer

We are building the next-gen AI-native, multilingual, Omni channel communication platform for emerging markets. We are looking for a hands-on AI/ML & Data Engineering Lead who will own and deliver critical components of our agent assist stack - including Whisper/STT, LangChain-based summarization, emotion tagging, GPT integration, and scalable data pipelines.

This is a foundational role blending applied machine learning, LLM integration, and modern data engineering to drive real-time decisioning and automation across the platform.

Key Responsibilities :

AI/ML + LLM/NLP :

- Lead implementation of LLM-based features : summarization, sentiment detection, auto-disposition, escalation tagging

- Fine-tune and evaluate models (Whisper, GPT, HuggingFace, Rasa) for vernacular (Indian) language support

- Build and deploy LangChain pipelines for prompt engineering, QA tagging, and agent assist

- Prototype emotion recognition, contextual agent replies, and real-time assist layer

- Build and maintain inference pipelines using FastAPI, Docker, Kubernetes

- Integrate AI modules into core product features (Dialer, CRM sync, IVR)

- Optimize model latency and deployment strategy for high concurrency environments

- Architect scalable data pipelines using PostgreSQL, Redis, and Kafka

- Build ETL/ELT workflows to support real-time analytics, dashboards, and feedback loops

- Maintain secure, compliant data storage, retrieval, and access control pipelines (DPDP, GDPR-ready)

Collaboration & Leadership :

- Work closely with Product, Engineering, and UX to deliver features that directly impact agent productivity

- Guide junior ML and data engineers; define and enforce coding/data standards

- Contribute to AI strategy, model governance, and data infrastructure roadmap

Required Skills & Qualifications :

- 5 years of experience in ML/AI/Data Engineering with exposure to LLMs and production-grade pipelines

- Hands-on with Whisper, LangChain, HuggingFace, or similar frameworks

- Solid Python (FastAPI preferred), SQL/PostgreSQL, and experience with RESTful APIs

- Proven experience with CI/CD, Docker, K3s/Kubernetes, Redis, Kafka/RabbitMQ

- Strong understanding of NLP/STT/TTS, summarization, and emotion tagging

- Ability to work in startup-paced environments with ownership mindset

Bonus Skills :

- Experience with multilingual models (Hindi, Tamil, Bengali)

- Exposure to Rasa, Coqui TTS, or OpenWA integrations

- Prior work in SaaS/Contact Center/Dialer/CRM ecosystems

- Familiarity with speech emotion recognition or agent coaching models


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