Machine Learning Engineer

Actively Reviewing the Applications

SourcingXPress

India, Haryana, Gurgaon Full-Time INR 15–18 LPA

Posted 2 days ago • Apply by June 28, 2026

Job Description

Company: CyberTrack Technology Solutions

Website: Visit Website

Business Type: Consulting Firm

Company Type: Service

Business Model: B2B

Funding Stage: Bootstrapped

Industry: Information Technology

Salary Range: ₹ 15-18 Lacs PA

Job Description

We are looking for an AI/ML Engineer with expertise in LLMs and NLP to build cutting-edge features for our contact center SaaS platform. You will work on LLM-based summarization, sentiment analysis, agent assist, and emotion recognition, integrating AI pipelines into core product features and ensuring scalable, production-grade deployment.

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, and 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 4-8 years
2-5 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 an ownership mindset

Bonus Skills