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Machine Learning Engineer - Search, Ranking & PersonalizationFuku • New York, New York, United States
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Machine Learning Engineer - Search, Ranking & Personalization

Fuku
  • US
    New York, New York, United States
  • US
    New York, New York, United States
Jetzt Bewerben

Über

Machine Learning Engineer – Search, Ranking & Personalization
Stage:
Seed
Founded:
2022
Key Job Information
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.
Requirements Must-Have Qualifications:
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.
Preferred Background:
Current or prior experience at companies like DoorDash, Etsy, Pinterest, Amazon, or eBay.
Previous work on consumer‑facing search or recommendation products.
Benefits & Perks
$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.
Interview Process
Intro call with Head of Recruiting
Technical Interview
Coding Interview
CTO Interview
Onsite Interview
Offer Extended
Hire
Candidate Guidelines Green Flags:
Experience solving large‑scale consumer search/ranking challenges (e.g., Pinterest, Meta, TikTok, Amazon Ads).
Strong track record shipping high‑impact ML features in consumer products.
Early‑stage or startup experience with end‑to‑end ownership of ML pipelines.
Demonstrated “builder” mindset—side projects, prototypes, hackathon wins.
High intrinsic motivation and interest in future entrepreneurship.
Red Flags:
Primarily B2B search experience with limited data complexity.
Research‑only background without production deployment.
Prefers management over hands‑on technical work.
Struggles with ambiguity or high‑intensity work environments.
Unwilling to relocate or adapt to NYC‑based team culture.
#J-18808-Ljbffr
  • New York, New York, United States

Sprachkenntnisse

  • English
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