APR Hub Technologies

We’re 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.