Who We Are

At adMarketplace, our mission is to deliver the most engaging consumer search experiences while empowering advertisers to measure media performance accurately. Today, millions of people worldwide engage with our exclusive, transparent media placements across the internet’s leading browsers, shopping apps, and review sites.

Our mantra at adMarketplace is to let our winners run. From your very first day at AMP, you’ll have the opportunity to start making a valuable contribution to our company. 

We’ve built our award-winning culture around five core values (known as our 5C’s): Curiosity, Collaboration, Creative Conflict, Commitment, and Competitiveness. With these guiding values, adMarketplace seeks to empower each and every employee to succeed, continue learning, and do their best work.

The Role

We are seeking an experienced AI/ML generalist who is passionate about building products in the search and ad technology ecosystem. As part of our well established AI/ML and Search organization, you will be pivotal in optimizing our AI-driven search and discovery app, integrating product feeds from various retailers and enhancing user experience through personalized search and recommendation systems. You will have a clear career progression path and numerous opportunities for both personal and professional growth in an intellectually stimulating and dynamic work environment.

Responsibilities

• Lead the development of AI/ML projects for our search and discovery application, from conceptualization to data procurement, model building, and deployment.
• Design and implement tracking and evaluation tools to assess model performance and data accuracy, focusing on product relevance based on user interaction feedback.
• Provide expert guidance in machine learning, deep learning, and advanced AI techniques, with a focus on e-commerce product search and recommendation systems.
• Provide thought leadership, subject matter expertise and serve as trusted advisor in machine learning, deep learning, and other state of the art AI techniques.
• Experience in contributing to high quality software at scale in a low latency environment.
• Translate research papers into high-quality, production-ready code.
• Take responsibility and ownership of features and drive key model architectural decisions.
• Communicate effectively, collaborate, and build long-term relationships across the organization.
• Mentor junior team members in achieving engineering excellence and be a change agent on the team.

Basic Qualifications

• A PhD with 5 years of experience or an MS with 5-8 years of experience in a quantitative field with experience building production systems or have equivalent experience working with large scale ML projects in industry.
• Proven expertise in building AI/ML models in at least one of the following domains: relevance, ranking, recommendation systems, and search within the e-commerce domain.
• Breadth and depth knowledge of statistical learning, machine learning, and deep learning.
• Experience in building distributed, low-latency, high-throughput batch and online ML services.
• Knowledge of how to deploy and maintain ML services in a production environment.
• Experience in designing and deploying feature engineering pipelines in production.
• Exposure to model monitoring and ML ops including containers and orchestration.
• Proficiency in Python or Java, and experience with Spark, Hadoop, SQL, and cloud services.
• Proficiency in ML packages like Tensorflow, PyTorch, scikit-learn, and Spark ML.
• Ability to operate efficiently in a high-paced, multi-functional, and rapidly evolving environment.

Preferred Qualifications

• 5+ years of experience in building ML models in the e-commerce product search space or recommender systems. Demonstrated ability to improve search relevance, product discovery, and user engagement through innovative ML techniques.
• Experience in fine-tuning pre-trained LLMs for specific e-commerce contexts or building custom LLMs to enhance user interaction and product discovery.
• Experience in building products using Generative AI powered autonomous agents.
• Deep understanding of how to leverage knowledge graphs in the context of e-commerce search and recommendation systems. Experience in integrating and utilizing knowledge graphs to improve product categorization, search accuracy, and personalized recommendations.
• Experience in building CTR/CVR prediction, ad selection, keyword bidding, and Learning to Rank models.

*Compensation Range: $170,000 - $220,000 

#LI-Onsite

Join Us

adMarketplace has been named as one of the best places to work in New York City by Built In and Crain’s- the latter of which have recognized us the past three years straight! AMP is currently experiencing triple digit growth, and it’s never been a better time to join our team!

We offer a robust continuing education program, management training, regular company-wide lunch and learns, and well-defined career paths to ensure all our employees have an opportunity to grow. 

At adMarketplace, we play to win, but we learn from our setbacks. Our commitment to a collaborative environment means no one succeeds alone, and no one fails alone either.   

We know you’ve come to expect comprehensive healthcare, wellness programs, paid time off, commuter benefits, and 401k matching from any company, so it’s a good thing we offer all of that and so much more. adMarketplace offers a dog friendly office, Summer Fridays, catered lunches, a fully stocked kitchen, ZogSports teams, happy hours and corporate retreats to encourage a strong work/life balance. 

Must be located or willing to relocate to New York City Metropolitan Area

*This range represents the low and high end of the base salary someone in this role may earn as an employee of adMarketplace in the New York office. Salaries will vary based on various factors including but not limited to professional and academic experience; training; associated responsibilities; and other business and organizational needs. The range listed is just one component of our total compensation package for employees. Salary decisions are dependent on the circumstances of each hire.