AI/ML Engineer / Data Scientist (AdTech / MarTech / Retail Media)
Role details
Job location
Tech stack
Job description
Develop and deploy AI/ML models for:
- Audience targeting & segmentation
- Ad ranking & bidding optimization
- Attribution & campaign performance modelling
- Fraud detection & anomaly detection
Build and optimize end-to-end ML pipelines:
- Data ingestion, feature engineering, training, and inference
- Batch & real-time model serving
Design real-time decisioning systems for high-throughput, low-latency environments.
Collaborate with data engineers and architects to ensure:
- Scalable data pipelines (ETL/ELT, streaming)
- High-quality feature stores and model lifecycle management
- Drive experimentation frameworks (A/B testing, causal inference) to continuously optimize performance metrics.
- Ensure privacy-aware and compliant AI solutions aligned with data governance frameworks.
Requirements
AI Engineer with 6-10 years of experience designing and deploying scalable AI/ML solutions for AdTech platforms covering targeting, bidding, personalization, attribution, and real-time analytics., Bachelor's/Master's in Computer Science, Data Science, AI/ML, or related field. 6-10 years of experience in AI/ML engineering / Data Science engineering roles. Strong programming skills in:
- Python (mandatory)
- Java or C++ (preferred)
Hands-on experience in:
- ML frameworks (TensorFlow, PyTorch, XGBoost)
- Distributed processing (Spark, Flink)
- Streaming systems (Kafka)
- SQL & NoSQL databases
Experience building production-grade ML pipelines and scalable data systems, Experience in AdTech / MarTech / Retail Media ecosystems Exposure to:
- Recommendation systems
- Real-time bidding systems
- Experimentation platforms / A/B testing
Familiarity with:
- Kubernetes, Docker, microservices
- Privacy and regulatory frameworks (GDPR, data compliance)