Lead Machine Learning Engineer

adMarketplace-posted 3 months ago
$240,000 - $280,000/Yr
Full-time • Senior
New York, NY
51-100 employees
Professional, Scientific, and Technical Services
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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 award-winning culture is built around five core values (known as our 5C's): Curiosity, Collaboration, Creative Conflict, Commitment, and Competitiveness. With these guiding values, adMarketplace seeks to empower our team to reach their full potential through continued learning, and the opportunity to do their best work. We are seeking an experienced Lead Machine Learning Engineer passionate about building impactful products in the search and advertising technology ecosystem. As part of our established AI/ML and Search organization, you will be instrumental in developing and optimizing advanced models to enhance our ultra-low-latency ad-serving platform and consumer-facing search solutions. You will collaborate closely with product, data science, and business teams, significantly contributing to strategic initiatives such as yield optimization, predictive modeling, and improved bidding performance. 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.

  • Drive end-to-end lifecycle management of AI/ML projects from concept and data acquisition to prototyping, model development, deployment, and ongoing maintenance.
  • Implement and champion best practices in MLOps, including data ingestion, model training pipelines, 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.
  • Mentor junior team members in achieving engineering excellence and be a change agent on the team.
  • PhD with 5+ years of experience or MS with 5-8+ years of industry experience in AI/ML, developing and deploying production-level ML systems.
  • Proven expertise in building AI/ML models in at least one of the following domains: Ads, relevance, ranking, recommendation systems, and search.
  • 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.
  • Hands-on experience in deploying and maintaining ML pipelines in production, including feature engineering and model monitoring frameworks.
  • Fluency in Python and proficiency with distributed frameworks (Spark, Hadoop), SQL, and cloud infrastructure.
  • 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.
  • 5+ years of experience in building ML models in the ads space or recommender systems.
  • Experience in building CTR/CVR prediction, ad selection, keyword bidding, and Learning to Rank models.
  • Experience in building and deploying online experimentation frameworks to identify right models and features at scale.
  • Experience in building ad selection frameworks using reinforcement learning or contextual bandits.
  • Experience in fine tuning LLMs or building them from scratch.
  • Experience in building products using Generative AI powered autonomous agents.
  • Comprehensive healthcare
  • Wellness programs
  • Paid time off
  • Commuter benefits
  • 401k matching
  • Summer Fridays
  • Catered lunches
  • Fully stocked kitchen
  • ZogSports teams
  • Happy hours
  • Corporate retreats
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