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# Senior AI/ML Engineer

- **Company:** TekWissen LLC
- **Location:** Atlanta, GA, United States
- **Experience:** Expert
- **Salary:** $197,600.0
- **Contract:** Temporary contract
- **Skills:** A/B Testing, Artificial Intelligence, Amazon Web Services, Big Data, Software as a Service, Continuous Integration, Graph Database, Python (Programming Language), Neo4j, Node.Js, Recommender Systems, Feature Engineering, Delivery Pipeline, Apache Spark, Deep Learning, Model Validation, Reliability of Systems, Backend, Pandas, Build Management, Pyspark, Apache Kafka, Machine Learning Operations
- **Published:** June 5, 2026
- **Apply:** https://www.careerjet.com/jobad/usba21bc80229a9d196893d163047905ab

## About the Role

* Python and experience with Pandas, PySpark Expertise in recommender systems (matrix factorization, deep learning, ranking models)
 * Experience in entity resolution / record linkage
 * Hands-on with graph modeling & graph databases (Neo4j, RDF, graph embeddings)
 * Strong understanding of ML lifecycle, experimentation, and evaluation metrics (NDCG, MAP, Precision/Recall)

Nice to Have

 * Experience with real-time ML systems and large-scale data (TB/PB)
 * Impact Drive personalized customer experiences, improve engagement & conversion, and enable data-driven decision-making at scale.

## Description

* Design and build collaborative, content-based, and hybrid recommendation systems
 * Develop real-time personalization pipelines and ranking models
 * Architect end-to-end ML systems (batch + streaming) with low-latency inference
 * Build customer knowledge graphs (Neo4j/Neptune) modeling users, products, and interactions
 * Enable Customer 360 insights and context-aware recommendations
 * Develop scalable pipelines using Python, Spark, Kafka Implement feature engineering, model training, and deployment workflows
 * Drive experimentation (A/B testing) and optimize for CTR, engagement, and conversion Ensure data quality, model performance, and system reliability
 * Apply MLOps practices (CI/CD, monitoring, model lifecycle management)
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