Talent Groups
AI Engineer– (AdTech or MarTech or Retail Media )
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI Engineer with 6–10 years of experience in AdTech, MarTech, or Retail Media. The contract length is unspecified, with a pay rate of "unknown." Key skills include Python, ML frameworks, and distributed processing.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
June 10, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Palo Alto, CA
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🧠 - Skills detailed
#Data Ingestion #SQL (Structured Query Language) #TensorFlow #Microservices #Cloud #Data Governance #Compliance #Scala #"ETL (Extract #Transform #Load)" #Computer Science #Docker #PyTorch #A/B Testing #Anomaly Detection #Java #Data Pipeline #Kafka (Apache Kafka) #Python #GDPR (General Data Protection Regulation) #Spark (Apache Spark) #ML (Machine Learning) #Databases #Data Science #Batch #C++ #NoSQL #Data Engineering #AI (Artificial Intelligence) #Programming #Kubernetes
Role description
Job Summary:
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:
• 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.
Required Skills:
• 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
Preferred Qualifications:
• 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)
Job Summary:
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:
• 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.
Required Skills:
• 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
Preferred Qualifications:
• 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)
