AI/ML Engineer / Data Scientist (AdTech / MarTech / Retail Media)

UnivEdge Consulting LLC
Menlo Park, United States of America
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Menlo Park, United States of America

Tech stack

Java
A/B testing
Artificial Intelligence
C++
Computer Programming
Data Governance
ETL
Data Systems
Distributed Computing Environment
Fraud Prevention and Detection
Python
Machine Learning
NoSQL
Recommender Systems
TensorFlow
SQL Databases
Feature Engineering
Data Ingestion
PyTorch
Spark
Kubernetes
Information Technology
Apache Flink
XGBoost
Kafka
Machine Learning Operations
Stream Processing
Data Pipelines
Docker
Microservices

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)

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