AI/ML Engineer

Role Overview

We are looking for an AI/ML Engineer to design and implement intelligent workflows powering our AdTech platforms — including SSP, DSP, and programmatic bidding systems. You’ll work on building AI-driven components that optimize ad delivery, targeting, pricing, and campaign performance. This role is ideal for candidates with at least 2+ years of hands-on experience in AI/ML and a passion for applying data-driven intelligence in AdTech environments.

Responsibilities

• Analyze existing AdTech workflows (SSP, DSP, bidding systems) and identify opportunities for AI/ML optimization.
• Design, implement, and fine-tune machine learning models to improve ad targeting, CTR prediction, bidding efficiency, and campaign ROI.
• Work with open-source AI/ML models and AWS AI/ML services to develop scalable AdTech solutions.
• Implement RAG (Retrieval-Augmented Generation) and other advanced AI strategies for data-driven campaign recommendations.
• Collaborate with Data Engineers, Analysts, and AdOps teams to leverage large-scale advertising and performance datasets.
• Monitor, retrain, and maintain production of ML models ensuring real-time accuracy and low latency.
• Support deployment and continuous improvement of AI/ML pipelines within programmatic advertising systems.

Requirements

• Strong understanding of AI/ML fundamentals, model development, and deployment strategies.
• Hands-on experience training and fine-tuning models (e.g., regression, classification, ranking, NLP).
• Familiarity with AdTech systems such as SSP, DSP, DMP, and RTB (Real-Time Bidding).
• Experience with AWS AI/ML services (SageMaker, Comprehend, Bedrock, etc.) or other cloud ML platforms.
• Proficiency in Python, TensorFlow, or PyTorch.
• Ability to analyze business and campaign data and convert them into scalable AI solutions.
• Minimum 3 years of experience in AI/ML model development and implementation.

Skills

• Python
• TensorFlow
• PyTorch
• AWS
• RAG

Nice to Have

• AWS Machine Learning Specialty or AI Practitioner certifications.
• Experience with RAG systems, LLMs, or Generative AI for AdTech use cases.
• Knowledge of MLOps and CI/CD pipelines for model deployment.
• Exposure to automated campaign optimization, bid strategy modeling, or user segmentation algorithms.

Benefits

• Flexible schedule