Senior AI/ML Engineer

BrickRed Systems; Frisco (TX); On-site; USD 150,000 - 230,000; Full time

Job summary

BrickRed Systems is seeking a Senior AI/ML Engineer to lead scalable AI/ML solutions for real-time personalization and recommendations. You will drive end-to-end ML systems, from feature engineering to deployment, working across ML engineering, data engineering, MLOps, and product teams.

The role emphasizes production-grade systems, knowledge graphs, and strong collaboration with cross-functional teams to optimize CTR, engagement, and business KPIs.

Qualifications

• Strong hands-on experience in AI/ML Engineering and production machine learning systems.
• Hands-on experience with Pandas and PySpark.
• Experience with collaborative filtering, content-based recommendations, hybrid models, matrix factorization, deep learning, and ranking models.
• Strong experience with Graph Modeling and graph databases such as Neo4j or Amazon Neptune.
• Experience with ML lifecycle, experimentation, model evaluation, and deployment.

Responsibilities

• Design and build collaborative, content-based, and hybrid recommendation systems.
• Develop real-time personalization pipelines and ranking models.
• Architect and implement end-to-end ML systems for batch and low-latency streaming inference.
• Build and maintain customer knowledge graphs using Neo4j and Neptune.
• Collaborate with Product, Data Engineering, Business, and other stakeholders to translate requirements into scalable AI/ML solutions.
• Mentor engineers and contribute to technical design and architecture decisions.

Skills

AI/ML Engineering

Python

Pandas

PySpark

Graph Modeling

Recommendation Systems

Entity Resolution

ML Lifecycle

Kafka

Tools

Neo4j

Amazon Neptune

Kafka

Spark

Job description

We are seeking a highly skilled Senior AI/ML Engineer to lead the design and deployment of scalable AI/ML solutions focused on real-time personalization, recommendation systems, and customer knowledge graphs.

The ideal candidate will have strong hands-on experience with Python, Pandas, PySpark, recommender systems, graph modeling, and graph databases, along with experience building production‑grade ML systems that drive measurable improvements in customer engagement, conversion, and personalization.

You will work across ML engineering, data engineering, MLOps, and product/business teams to build scalable batch and real‑time ML solutions and deliver context‑aware recommendations at scale.

Key Responsibilities

• Design and build collaborative, content‑based, and hybrid recommendation systems.
• Develop real‑time personalization pipelines and ranking models.
• Architect and implement end‑to‑end ML systems supporting both batch processing and low‑latency streaming inference.
• Build and maintain customer knowledge graphs using technologies such as Neo4j and Amazon Neptune.
• Model relationships between customers, users, products, interactions, and behavioral data.
• Enable Customer 360 insights and context‑aware recommendations.
• Develop scalable data and ML pipelines using Python, Spark, and Kafka.
• Perform feature engineering, model training, evaluation, and deployment.
• Implement and optimize recommendation algorithms including matrix factorization, deep learning, and ranking models.
• Drive experimentation through A/B testing and optimize models for CTR, engagement, conversion, and other business KPIs.
• Implement entity resolution and record linkage capabilities.
• Apply MLOps practices, including CI/CD, model monitoring, model lifecycle management, and production reliability.
• Monitor data quality, model performance, scalability, and system reliability.
• Work with large‑scale data environments and design solutions capable of handling high‑volume workloads.
• Collaborate with Product, Data Engineering, Business, and other technical stakeholders to translate business requirements into scalable AI/ML solutions.
• Mentor junior and mid‑level engineers and contribute to technical design and architecture decisions.

Required Qualifications

• Strong hands‑on experience in AI/ML Engineering and production machine learning systems.
• Hands‑on experience with Pandas and PySpark.
• Experience with collaborative filtering, content‑based recommendations, hybrid models, matrix factorization, deep learning, and ranking models.
• Strong experience with Graph Modeling.
• Hands‑on experience with graph databases such as Neo4j or Amazon Neptune.
• Experience with RDF, graph embeddings, or related graph technologies.
• Experience with Entity Resolution / Record Linkage.
• Strong understanding of ML lifecycle, experimentation, model evaluation, and deployment.
• Experience with recommendation evaluation metrics such as NDCG, MAP, Precision, and Recall.
• Experience developing scalable pipelines using Python, Spark, and Kafka.
• Experience with feature engineering, model training, and production deployment.
• Strong understanding of MLOps, CI/CD, monitoring, and model lifecycle management.
• Ability to build and support production‑grade AI/ML solutions, not just research prototypes.
• Strong problem‑solving and analytical skills.
• Excellent communication and collaboration skills.

Preferred Qualifications

• Experience building real‑time ML and personalization systems.
• Experience working with large‑scale TB/PB data environments.
• Experience with low‑latency model serving and real‑time inference.
• Experience with Customer 360, customer intelligence, or behavioral analytics.
• Experience with streaming technologies such as Kafka.
• Experience with graph embeddings and knowledge graph solutions.
• Experience optimizing recommendation systems for CTR, engagement, conversion, and personalization.
• Strong experience working with cross‑functional Product, Data, Engineering, and Business teams.
• Experience mentoring engineers and leading technical initiatives.

Mandatory Skills

AI/ML | Python | Pandas | Graph Modeling | Recommendation Systems | PySpark | Neo4j/Neptune | Entity Resolution | ML Lifecycle

ABOUT BRICKRED SYSTEMS

BrickRed Systems is a global leader in next‑generation technology consulting and workforce solutions, specializing in delivering high‑quality talent across digital, engineering, marketing, analytics, finance, operations, and business transformation domains. With a strong emphasis on innovation, scalability, and client success, BrickRed Systems helps organizations solve complex business challenges by providing skilled professionals across strategy, technology, creative, and operational functions. BrickRed fosters a culture of continuous learning, collaboration, and excellence, enabling professionals to contribute to high‑impact global initiatives while advancing their careers.