The Machine Learning Engineer II role at adMarketplace focuses on building, optimizing, and operating advanced AI/ML models for ultra-low-latency ad-serving and consumer-facing search. The position includes end-to-end ownership across the ML lifecycle, with emphasis on reliable deployment and experimentation to improve relevancy and bidding performance.
Key Responsibilities
- Own AI/ML projects end-to-end, from concept and data acquisition through prototyping, model development, deployment, optimization, and ongoing maintenance.
- Drive MLOps best practices, including data collection, model training pipelines, deployments, monitoring, alerting, and QA to support dependable model performance.
- Participate in major model architecture decisions using state-of-the-art approaches across machine learning, deep learning, and reinforcement learning.
- Build and deploy feature engineering pipelines and ML services designed for low latency and high throughput.
- Create and run A/B testing and experimentation frameworks to evaluate improvements and iterate on model performance.
- Design, build, and maintain production software systems and microservices supporting AI/ML applications, emphasizing reliability, scalability, low latency, and high throughput.
- Communicate effectively and collaborate across the organization to build long-term working relationships.
Required Qualifications
- 3+ 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 domain: 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 with Python, plus proficiency with distributed frameworks (Spark, Hadoop), SQL, and cloud infrastructure.
- 2+ years of experience with ML packages including Tensorflow or PyTorch, scikit-learn, and Spark ML.
- Ability to work effectively in a high-paced, multi-functional, rapidly evolving environment.
Technologies
- Python, Spark, Hadoop, SQL
- Cloud infrastructure
- Tensorflow, PyTorch, scikit-learn, Spark ML
- Microservices
Preferred Qualifications
- 3+ 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+ years of experience building products using Generative AI powered autonomous agents.
Compensation
$145,000 - $175,000 USD per year plus Bonus and Equity.
The listed range reflects the low and high end of base salary for this role in the New York office. Salary can vary based on factors including professional and academic experience, training, responsibilities, and business needs. The range is one component of the total compensation package, and salary decisions depend on the circumstances of each hire.
Benefits
- Comprehensive healthcare
- Wellness programs
- Paid time off
- Commuter benefits
- 401k matching
- Summer Fridays
- Catered lunches
- A fully stocked kitchen
- ZogSports teams
- Happy hours
- Corporate retreats
- Robust continuing education program
- Management training
- Regular company-wide lunch and learns
- Well-defined career paths
Additional Information
- Location: New York, NY (onsite)
- adMarketplace has been named one of the best places to work in New York City by Built In and Crain’s, with recognition for three consecutive years.
- No Third Party Recruiters: adMarketplace does not accept unsolicited agency resumes and is not responsible for any fees related to unsolicited resumes.
About the Role
This position supports ad-serving and consumer search applications, combining end-to-end ML lifecycle ownership with MLOps, scalable low-latency ML systems, and experimentation workflows designed to improve relevancy and bidding outcomes. adMarketplace is also experiencing triple digit growth.
