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adMarketplace

Lead Machine Learning Engineer

Reposted Yesterday
In-Office
New York, NY
240K-260K Annually
Senior level
In-Office
New York, NY
240K-260K Annually
Senior level
As a Lead Machine Learning Engineer, you'll manage AI/ML projects, optimize models, enhance ad-serving platforms, and mentor junior engineers.
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Who We Are

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 – our 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 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 and applications to enhance our ultra-low-latency ad-serving platform and consumer-facing search solutions. 

You will collaborate closely with product, business, and other engineering teams, making significant contributions 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 both personal and professional growth in an intellectually stimulating and dynamic work 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.

  • Mentor junior team members in achieving engineering excellence and be a change agent on the team.

Basic Qualifications

  • PhD with 5+ years of experience or MS with 5-8+ years of industry experience in AI/ML, developing and deploying production-grade ML systems.

  • 2+ years of experience in building AI/ML models in at least one of the following domains: Ads, relevance, ranking, recommendation systems, and search.

  • 3+ years of experience in building distributed, low-latency, high-throughput batch and online ML services.

  • 3+ years of experience in 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 in 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 in building and deploying online experimentation frameworks to identify right models and features at scale.

  • 2+ years of experience in building ad selection frameworks using reinforcement learning or contextual bandits.

  • Experience in fine tuning LLMs.

  • 1+ years of experience in building products using Generative AI powered autonomous agents.

Compensation: $240,000 - $260,000 + Bonus & Equity

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 Summer Fridays, catered lunches, a fully stocked kitchen, ZogSports teams, happy hours and corporate retreats to encourage a strong work/life balance. 

No Third Party Recruiters. We do not accept unsolicited agency resumes and we are not responsible for any fees related to unsolicited resumes. 

*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.

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