Senior Machine Learning Engineer

adMarketplace is the largest global marketplace for Native Search advertising. For over 25 years, we’ve connected brands with consumers at the moment they express commercial intent beyond legacy search engines. Today, our Native Search solutions are exclusively integrated across next‑generation platforms where discovery happens, including web browsers, Buy Now Pay Later apps, and AI chat surfaces. Powered by vector search technology, our platform delivers relevant text and product ads that match consumers with the brands, products, and offers they’re actively seeking. Our award‑winning culture is grounded in the principles of Curiosity, Collaboration, Creative Conflict, Commitment, and Competitiveness – the 5Cs. These values drive us to turn complexity into clarity and create measurable value for consumers, advertisers, and publishers alike. The Role We are seeking an experienced Senior Machine Learning Engineer passionate about building impactful products in the search and advertising technology ecosystem. As part of our AI/ML and Search organization, you will develop and optimize advanced models and applications to enhance our ultra‑low‑latency ad‑serving platform and consumer‑facing search solutions. You will collaborate closely with product, business, and engineering teams, contributing to strategic initiatives such as relevancy & yield optimization, predictive modeling, and improved bidding performance. You will have a clear career progression path and numerous opportunities for growth in an intellectually stimulating and dynamic environment. Responsibilities Drive end‑to‑end lifecycle management of AI/ML projects from concept and data acquisition to prototyping, model development, deployment, optimization and ongoing maintenance. Implement and champion best practices in MLOps, including data collection, model training pipelines, model deployments, monitoring, alerting, and QA to ensure model reliability and performance. Contribute significantly to model architecture decisions, leveraging state‑of‑the‑art machine learning, deep learning, and reinforcement learning techniques. Develop and deploy robust feature engineering pipelines and ML services optimized for low latency and high throughput. Establish and utilize robust A/B testing and experimentation frameworks to evaluate and iteratively improve model performance. Translate research papers into high‑quality, production‑ready code. Communicate effectively, collaborate, and build long‑term relationships across the organization. Basic Qualifications PhD with 3+ years of experience or MS with 3‑5+ years of industry experience in AI/ML, developing and deploying production‑grade ML systems. 2+ years of experience building AI/ML models in at least one of the following domains: Ads, relevance, ranking, recommendation systems, and search. 3+ years of experience building distributed, low‑latency, high‑throughput batch and online ML services. 3+ years of experience deploying and maintaining ML pipelines in production, including feature engineering and model monitoring frameworks. 2+ years of experience in Python and proficiency with distributed frameworks (Spark, Hadoop), SQL, and cloud infrastructure. 2+ years of experience with ML packages such as Tensorflow or 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 building ML models for ads, search and/or recommender systems including CTR/CVR prediction, ad selection, keyword bidding, and Learning to Rank models. 2+ years of experience building and deploying online experimentation frameworks to identify right models and features at scale. 2+ years of experience building ad selection frameworks using reinforcement learning or contextual bandits. Experience in fine tuning LLMs. 1+ year of experience building products using Generative AI‑powered autonomous agents. Compensation $170,000 - $240,000 + Bonus & Equity This range represents the low and high end of the base salary in the New York office. Salaries will vary based on professional and academic experience, training, responsibilities, and other business and organizational needs. The range listed is one component of the total compensation package. Salary decisions are dependent on circumstances of each hire. Benefits Comprehensive healthcare, wellness programs, paid time off, commuter benefits, 401(k) matching, and additional benefits such as flexible work hours, catered lunches, and wellness perks are offered. #J-18808-Ljbffr adMarketplace