ML Engineer

Job Title: Machine Learning Engineer - Recommendation Systems (Consumer Marketing)
Location: Parsippany-Troy Hills, NJ (Hybrid: 3 days onsite)
Job Type: C2C

About the Role
Join ADP's dynamic Consumer Marketing team as a Machine Learning Engineer focused on cutting-edge recommendation systems. Drive innovation by designing and scaling advanced models that personalize customer experiences, accelerate engagement, and fuel revenue growth. Collaborate with experts across business, marketing, product, and engineering to shape the future of consumer marketing technology.

Responsibilities

- Architect and implement machine learning models for recommendation and personalization (collaborative filtering, deep learning, hybrid techniques)
- Optimize large-scale models for real-time prediction, performance, and scalability
- Collaborate with cross-functional teams to integrate models into production and campaign pipelines
- Analyze and enhance model quality using key metrics: precision, recall, click-through rate, conversion, and customer lifetime value
- Leverage behavioral, segmentation, and first-party marketing data to improve personalization
- Research and experiment with advanced techniques such as graph neural networks, DeepFM, reinforcement learning, and contextual bandits to boost recommendation performance

Required Skills and Experience

- 5+ years hands-on experience in machine learning, specializing in recommendation systems within consumer-facing domains
- Proven success building and deploying personalization models that delivered measurable business outcomes
- Deep expertise in neural networks, ranking systems, matrix factorization, and graph-based methods
- Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch)
- Solid experience with consumer, behavioral, and marketing data
- Familiarity with Databricks and AWS
- Excellent problem-solving skills; collaborative, customer-centric mindset

Preferred Skills

- Experience with consumer data platforms (CDPs), marketing analytics, or A/B testing
- Background in agentic AI frameworks and large language models (LTMs) tailored for recommender systems

Benefits

- Opportunity to work with industry leaders and shape innovative consumer marketing solutions
- Hybrid workplace with a collaborative, growth-focused environment
- Exposure to the latest tools and technologies in machine learning and marketing science

How to Apply

- Submit your resume and brief cover letter highlighting your experience with recommendation systems and consumer marketing data.
- Interview Process: Introductory call (fit/communication), technical interview (no coding test), final onsite interview with leadership team.

Take the next step in your machine learning career-apply today and help redefine how customers experience personalized marketing.