Senior AI/ML Engineer

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.