Harnham
Principal Machine Learning Engineer - Recommendation & Relevancy
Location:
New York (Hybrid - 4 days onsite)
Compensation:
$600,000 - $1,500,000 total package
(Base Salary: $360,000-$400,000 + Equity + Exceptional Benefits)
THE COMPANY
Join a hyper-growth global e-commerce innovator that's reshaping how businesses deliver real-time, personalized experiences at the point of purchase. Leveraging cutting-edge AI and ML at massive scale, this organization is building the future of intelligent commerce-and you could be a key part of it.
With explosive growth, a high-caliber team, and a tech-first culture, this is a unique opportunity to drive meaningful impact in a fast-paced, data-driven environment.
THE ROLE
As a
Principal Machine Learning Engineer , you'll drive the design and deployment of large-scale, intelligent decision-making systems. From personalized recommendations to smart bidding and real-time optimization, your work will directly influence millions of transactions and customer experiences daily.
You'll collaborate closely with product and engineering partners to build ML solutions that are both cutting-edge and production-ready.
Key Focus Areas: Smart bidding and budget pacing algorithms Real-time recommendation engines Lookalike modeling and customer targeting CTR/CVR modeling and conversion optimization Responsibilities:
Architect and deploy end-to-end ML solutions at scale Develop robust data pipelines, feature stores, and orchestration frameworks Build high-performance, production-grade ML models (batch & real-time) Lead experimentation (offline & online), including A/B testing and model tuning Drive engineering excellence with well-tested, maintainable, scalable code Mentor team members and contribute to a culture of technical growth YOUR SKILLS & EXPERIENCE
PhD or Master's degree in Machine Learning, Computer Science, or a related field 10+ years of hands-on experience building production ML systems at scale Expertise in AWS, TensorFlow, Feature Store technologies, and orchestration tools (e.g., Kubeflow, Airflow) Deep knowledge of at least two of the following: Bayesian methods Recommender systems Multi-task or meta-learning CTR/CVR prediction models Bonus:
Experience with advanced model architectures like Deep & Cross Network v2, Multi-gate Mixture-of-Experts, or Deep & Wide Networks.
BENEFITS
Significant equity in a high-growth tech company Premium, fully covered health insurance (you + family) 401(k) with 4% dollar-for-dollar match Catered lunches and daily snacks Global travel opportunities Inclusive, collaborative culture with a strong focus on innovation, diversity, and impact
HOW TO APPLY
Ready to solve real-world problems at scale and push the boundaries of applied machine learning? Apply now to speak with one of our specialist recruiters and learn more about this high-impact opportunity.
Location:
New York (Hybrid - 4 days onsite)
Compensation:
$600,000 - $1,500,000 total package
(Base Salary: $360,000-$400,000 + Equity + Exceptional Benefits)
THE COMPANY
Join a hyper-growth global e-commerce innovator that's reshaping how businesses deliver real-time, personalized experiences at the point of purchase. Leveraging cutting-edge AI and ML at massive scale, this organization is building the future of intelligent commerce-and you could be a key part of it.
With explosive growth, a high-caliber team, and a tech-first culture, this is a unique opportunity to drive meaningful impact in a fast-paced, data-driven environment.
THE ROLE
As a
Principal Machine Learning Engineer , you'll drive the design and deployment of large-scale, intelligent decision-making systems. From personalized recommendations to smart bidding and real-time optimization, your work will directly influence millions of transactions and customer experiences daily.
You'll collaborate closely with product and engineering partners to build ML solutions that are both cutting-edge and production-ready.
Key Focus Areas: Smart bidding and budget pacing algorithms Real-time recommendation engines Lookalike modeling and customer targeting CTR/CVR modeling and conversion optimization Responsibilities:
Architect and deploy end-to-end ML solutions at scale Develop robust data pipelines, feature stores, and orchestration frameworks Build high-performance, production-grade ML models (batch & real-time) Lead experimentation (offline & online), including A/B testing and model tuning Drive engineering excellence with well-tested, maintainable, scalable code Mentor team members and contribute to a culture of technical growth YOUR SKILLS & EXPERIENCE
PhD or Master's degree in Machine Learning, Computer Science, or a related field 10+ years of hands-on experience building production ML systems at scale Expertise in AWS, TensorFlow, Feature Store technologies, and orchestration tools (e.g., Kubeflow, Airflow) Deep knowledge of at least two of the following: Bayesian methods Recommender systems Multi-task or meta-learning CTR/CVR prediction models Bonus:
Experience with advanced model architectures like Deep & Cross Network v2, Multi-gate Mixture-of-Experts, or Deep & Wide Networks.
BENEFITS
Significant equity in a high-growth tech company Premium, fully covered health insurance (you + family) 401(k) with 4% dollar-for-dollar match Catered lunches and daily snacks Global travel opportunities Inclusive, collaborative culture with a strong focus on innovation, diversity, and impact
HOW TO APPLY
Ready to solve real-world problems at scale and push the boundaries of applied machine learning? Apply now to speak with one of our specialist recruiters and learn more about this high-impact opportunity.