Exp – Total exp 7-13yrs and AI Exp - 4 yrs.

Work from office – Gurgoan /  Bangalore [2nd oPtion]

Look for exp in Voice Bot Development, LLM, NLP, RAG, Python, Fast API Creation

creation, budget 25 – 28 LPA [max]

Immediate joiner – max 20 days

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

Total experience of 10-13 years

•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

Why Join Us?

•Shape the AI-native dialer experience agents across India and Oversees

•Build with purpose — multilingual, affordable, fast-deploy SaaS platform for emerging markets

•Work with modern tech: GPT, Whisper, LangChain, WebRTC, React, FastAPI

•Equity + flexible remote working + startup velocity

Exp – Total exp 7-13yrs and AI Exp - 4 yrs.

Work from office – Gurgoan /  Bangalore [2nd oPtion]

Look for exp in Voice Bot Development, LLM, NLP, RAG, Python, Fast API Creation

creation, budget 25 – 28 LPA [max]

Immediate joiner – max 20 days

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

Total experience of 10-13 years

•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

Why Join Us?

•Shape the AI-native dialer experience agents across India and Oversees

•Build with purpose — multilingual, affordable, fast-deploy SaaS platform for emerging markets

•Work with modern tech: GPT, Whisper, LangChain, WebRTC, React, FastAPI

•Equity + flexible remote working + startup velocity