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.
Strong Python programming skills.
Hands-on experience with Pandas and PySpark

.
Proven expertise in Recommendation Systems / Recommender Systems

.
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

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.

Job description