c++
docker
java
kafka
kubernetes
python
pytorch
spark
tensorflowRole: AI Scientist – AdTech
Location: USA (Remote)
Job Description
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.
The role requires strong engineering fundamentals with hands-on ML model development, data pipelines, and real-time decision systems, leveraging modern distributed and cloud-based architectures.
Key Responsibilities
• Develop and deploy AI/ML models for:
o Audience targeting & segmentation
o Ad ranking & bidding optimization
o Attribution & campaign performance modelling
o Fraud detection & anomaly detection
• Build and optimize end-to-end ML pipelines:
o Data ingestion, feature engineering, training, and inference
o Batch & real-time model serving
• Design real-time decisioning systems for high-throughput, low-latency environments.
• Collaborate with data engineers and architects to ensure:
o Scalable data pipelines (ETL/ELT, streaming)
o 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.
Required Qualifications
• 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:
o Python (mandatory)
o Java or C++ (preferred)
• Hands-on experience in:
o ML frameworks (TensorFlow, PyTorch, XGBoost)
o Distributed processing (Spark, Flink)
o Streaming systems (Kafka)
o SQL & NoSQL databases
• Experience building production-grade ML pipelines and scalable data systems
Preferred Qualifications
• Experience in AdTech / MarTech / Retail Media ecosystems
• Exposure to:
o Recommendation systems
o Real-time bidding systems
o Experimentation platforms / A/B testing
• Familiarity with:
o Kubernetes, Docker, microservices
o Privacy and regulatory frameworks (GDPR, data compliance)