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AI Engineer

Job

Talent Groups

Menlo Park, CA (In Person)

Full-Time

Posted 3 days ago (Updated 13 hours ago) • Actively hiring

Expires 7/13/2026

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Job Description

We are looking for an AI Engineer with 12+ years of experience in The candidate will have strong expertise in Python, machine learning model development, real-time data processing, and distributed systems. Hands-on experience with TensorFlow, PyTorch, Spark, Kafka, ML pipelines.
Job Description:
AI Engineer with 10-12 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 Qualifications Bachelor s/Master s in Computer Science, Data Science, AI/ML, or related field. 10-12 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)