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Machine Learning Engineer - Search, Ranking & Personalization - Full-time
Fuku
Anywhere•Remote•3-6 Yrs•3 days ago
Job description
Remote
Overview
• Machine Learning Engineer – Search, Ranking & Personalization* • Stage:* Seed • Founded:* 2022
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.
- 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.
Qualifications
- *Salary Range:* $190,000 – $260,000 per year
- *Equity:* Competitive equity package
- *Visa Sponsorship:* H-1B, O-1, OPT
- About the Company*
- Role Summary*
- 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.
- 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.
- Ideal Companies*
- Amazon
- eBay
- DoorDash
Benefits
- $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:*
- $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:*