Ai Ml Engineer

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.