ZipRecruiter
Job Description
STAFF MACHINE LEARNING ENGINEER
Hybrid – Bay Area (3 Days/Week Onsite)
$280,000 – $315,000 Base + Bonus + Equity
About the Company
We’re a fast-growing online marketplace backed by a major global tech player. Our platform helps millions of people buy and sell items in a way that feels social, personalized, and community-driven.
With a strong base of engaged users on both the buying and selling side, we're investing heavily in AI and machine learning to improve product discovery, build smarter seller tools, and make the platform safer and more enjoyable for everyone. We're now growing our ML Engineering team to help make these experiences smarter, faster, and more scalable.
About the Role
We're looking for a
Staff Machine Learning Engineer
to lead some of the most critical AI/ML initiatives across our platform. You’ll be responsible for designing and building machine learning systems that impact millions of users — from personalized recommendations and smarter search to seller tools and fraud detection.
This is a high-impact, hands-on role best suited for someone with deep experience in ML systems who wants to own projects end-to-end and help shape the future of a fast-moving, high-scale marketplace.
What You’ll Be Doing
Lead development of core ML systems that power recommendations, personalization, and trust & safety
Design both batch and real-time pipelines that take models from experimentation to full production
Collaborate with data scientists to turn prototypes into scalable, production-ready models
Improve and maintain our MLOps systems (serving, monitoring, retraining, etc.)
Help set technical direction across multiple teams and mentor other engineers
Partner with product and infrastructure teams to drive big-picture decisions
Our Tech Stack
& Frameworks:
Python, PyTorch, TensorFlow
Tools:
Airflow, Spark, MLFlow, Databricks, Feature Store
Infrastructure:
AWS + GCP, supporting real-time and batch workflows
Model Serving:
Vector databases, scalable inference pipelines, model monitoring tools
What We’re Looking For
7+ years of engineering experience, including 3+ years working on ML systems in production
Deep experience building and scaling recommendation, search, or personalization systems
Strong understanding of distributed systems, model performance, and production deployment
Able to design systems that balance speed, reliability, and cost
Bonus: experience working on large-scale marketplaces, e-commerce, or other consumer platforms
Why You’ll Love It Here
You’ll join a small but mighty team making a real difference in how people shop, discover, and sell online. You’ll have the freedom to lead major projects, contribute to technical strategy, and see your work drive real business results — all within a supportive, fast-paced environment.
STAFF MACHINE LEARNING ENGINEER
Hybrid – Bay Area (3 Days/Week Onsite)
$280,000 – $315,000 Base + Bonus + Equity
About the Company
We’re a fast-growing online marketplace backed by a major global tech player. Our platform helps millions of people buy and sell items in a way that feels social, personalized, and community-driven.
With a strong base of engaged users on both the buying and selling side, we're investing heavily in AI and machine learning to improve product discovery, build smarter seller tools, and make the platform safer and more enjoyable for everyone. We're now growing our ML Engineering team to help make these experiences smarter, faster, and more scalable.
About the Role
We're looking for a
Staff Machine Learning Engineer
to lead some of the most critical AI/ML initiatives across our platform. You’ll be responsible for designing and building machine learning systems that impact millions of users — from personalized recommendations and smarter search to seller tools and fraud detection.
This is a high-impact, hands-on role best suited for someone with deep experience in ML systems who wants to own projects end-to-end and help shape the future of a fast-moving, high-scale marketplace.
What You’ll Be Doing
Lead development of core ML systems that power recommendations, personalization, and trust & safety
Design both batch and real-time pipelines that take models from experimentation to full production
Collaborate with data scientists to turn prototypes into scalable, production-ready models
Improve and maintain our MLOps systems (serving, monitoring, retraining, etc.)
Help set technical direction across multiple teams and mentor other engineers
Partner with product and infrastructure teams to drive big-picture decisions
Our Tech Stack
& Frameworks:
Python, PyTorch, TensorFlow
Tools:
Airflow, Spark, MLFlow, Databricks, Feature Store
Infrastructure:
AWS + GCP, supporting real-time and batch workflows
Model Serving:
Vector databases, scalable inference pipelines, model monitoring tools
What We’re Looking For
7+ years of engineering experience, including 3+ years working on ML systems in production
Deep experience building and scaling recommendation, search, or personalization systems
Strong understanding of distributed systems, model performance, and production deployment
Able to design systems that balance speed, reliability, and cost
Bonus: experience working on large-scale marketplaces, e-commerce, or other consumer platforms
Why You’ll Love It Here
You’ll join a small but mighty team making a real difference in how people shop, discover, and sell online. You’ll have the freedom to lead major projects, contribute to technical strategy, and see your work drive real business results — all within a supportive, fast-paced environment.