Ai Ml Engineer

1 week ago

Chennai Hyderabad, India e7526782-b3f0-4c3b-8a10-3bae03d1deb6 Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Were building a new MarTech intelligence platform that combines marketing analytics, predictive modeling, and AI-powered insights. We're looking for an AI/ML Engineer who can transform raw marketing data into intelligence from predictive analytics to RAG-enabled chat experiences.

This is a deeply technical, hands-on ML engineering role where you'll work across modeling, data pipelines, and agentic AI capabilities.

What You'll Own

  • Designing and deploying marketing prediction models (CPC/CAC/ROAS forecasting, MMM signals, etc.).
  • Building analytics chatbots, RAG pipelines, and agentic workflows.
  • Working closely with data and engineering to stitch AI capabilities into production.
  • Converting marketing business logic into ML-driven insights.

Core Requirements (Must-Have)

1. MarTech + Data Understanding

You must be fluent in marketing data structures and analytics signals:

  • Understanding of segmentation, attribution, MMM fundamentals.
  • Experience with pixel-level and server-side tracking data.
  • Strong grasp of MarTech KPIs and funnel metrics.
  • Ability to process large-scale, multi-source marketing datasets.

2. AI/ML Engineering

You should be hands-on with:

  • Predictive analytics and time-series forecasting.
  • Natural language or analytics-focused chatbots.
  • RAG pipelines: retrieval, embeddings, indexing, prompt engineering.
  • Agent-based automation workflows (CrewAI, LangGraph, or similar).
  • Building production-grade ML pipelines and data prep workflows.

3. Backend + Integration Familiarity

(Not deep expertise, but comfortable enough to work with engineering)

  • REST/GraphQL API consumption.
  • Working with event streams, warehousing, ETL, and transformations.
  • Understanding of RBAC, authentication, and secure data access patterns.

Bonus Points

Not required, but very strong plus:

  • Experience building WhatsApp bots or conversational engines.
  • Ability to translate complex AI/ML outputs into simple product experiences.
  • AWS or cloud familiarity for AI/ML deployment.
  • Experience with gRPC or webhook-based automation triggers.

What You Get

  • Ownership of core AI features such as prediction, intelligence, automation.
  • Ability to ship models into production on a greenfield stack.
  • Work directly with the founder on product strategy for AI.
  • Competitive salary + performance-based ESOP potential.

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