Machine Learning Engineer - Search, Ranking, and Personalization
Visa Sponsorship
Remote
AI Summary
Join our team as a Machine Learning Engineer to design, build, and scale machine learning systems for search, ranking, and personalization. With 3+ years of experience, you'll collaborate with a world-class team to drive user retention and trust. You'll work on large-scale search, ranking, and personalization models, integrating with backend and infrastructure teams.
Key Highlights
Design, train, and deploy large-scale search, ranking, and personalization models
Collaborate with backend and infrastructure teams
Continuously improve model accuracy and system scalability
Technical Skills Required
Benefits & Perks
$190K–$260K base salary
Competitive equity
Direct impact on a core product
Work alongside top-tier engineers
Fast-paced startup culture
Job Description
Job Description
Machine Learning Engineer - Search, Ranking & Personalization
Location: New York, NY / San Francisco, CA (Remote OK)
Employment Type: Full-Time
Experience Level: 3+ years
Salary Range: $190,000 – $260,000 per year
Equity: Competitive equity package
Visa Sponsorship: H-1B, O-1, OPT
About The Company
Client is a fast-growing shopping platform with over 350,000 active users and a 90% retention rate. The company is focused on building intelligent, personalized search and ranking systems to help users discover and trust products at scale. The team is composed of experienced engineers from leading consumer tech companies such as Pinterest and Amazon.
Role Summary
As a Machine Learning Engineer at Client's company, you will join the ML team to design, build, and scale machine learning systems that drive search, ranking, and personalization across a platform serving hundreds of millions of items daily. This is a highly impactful role where your work directly influences user retention and trust. You will collaborate with a world-class team of engineers and play a key part in defining the ML search and personalization strategy from the ground up. The position is open to fully remote candidates.
Key Responsibilities
- Design, train, and deploy large-scale search, ranking, and personalization models.
- Handle hundreds of millions of items daily with high performance and reliability.
- Collaborate closely with backend and infrastructure teams to integrate ML models into production (GraphQL, Prisma, Node.js, Python, gRPC/Protobuf).
- Continuously improve model accuracy and system scalability.
- Contribute to product direction and technical roadmap for Client's ML systems.
- Minimum of 3+ years professional experience building and deploying ML models in production.
- Proven experience with ranking, recommendation, or personalization systems.
- Proficiency in PyTorch and large-scale data processing for real-time inference.
- Strong backend integration experience (GraphQL, Prisma, Node.js, Python, gRPC/Protobuf).
- Willingness to work in a high-intensity, fast-paced startup environment.
- Based in New York or remote in San Francisco.
- Current or prior experience at companies like DoorDash, Etsy, Pinterest, Amazon, or eBay.
- Previous work on consumer-facing search or recommendation products.
- $190K–$260K base salary plus competitive equity.
- Direct impact on a core product with a massive, high-retention user base.
- Work alongside top-tier engineers from leading consumer tech companies.
- Fast-paced startup culture with rapid iteration and experimentation.
- Opportunity to build the ML search and personalization strategy from scratch.