Machine Learning Engineer – Recommendation Systems (Consumer Marketing)
Location: Parsippany, NJ - Hybrid
Duration: 12+ Months
Interview process- Video + F2F meeting.
Must haves:
•Recommendation Systems/ Ranking Systems
•Neural networks
•DeepLearning
•GRAPH
•DeepFM
•Matrix factorization
Requirements:
•5+ years of experience in machine learning, with a focus on recommendation systems, ideally within consumer marketing, retail, e-commerce, or a related consumer-facing domain.
•Proven track record building personalization or recommendation models that measurably improved engagement or marketing performance.
•Proficiency in Python, TensorFlow, PyTorch, or similar ML frameworks.
•Strong understanding of algorithms like matrix factorization, neural networks, and ranking systems.
•Strong understanding of LTMs and agentic AI frameworks that can be customized for recommender systems
•Experience working with consumer/marketing data, including behavioral, transactional, and campaign data (familiarity with CDPs, marketing analytics, or A/B testing is a plus).
•Experience with Databricks and AWS.
•Excellent problem-solving skills and a passion for delivering impactful, customer-centric solutions.
