Senior AI/ML Engineer

Job not on LinkedIn

🔥 3 minutes ago

🗽 New York, Massachusetts – Remote

🗽 New York – Remote 🍂 Massachusetts – Remote

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Nivoda

WebsiteLinkedInAll Job Openings

201 - 500 employees

🛒 Retail

🛍️ eCommerce

🏪 Marketplace

💰 $30M Series B on 2024-05

Retail • eCommerce • Marketplace

Nivoda is an innovative company that offers the world's largest collection of natural diamonds, lab-grown diamonds, and gemstones. They provide retail solutions that make purchasing diamonds as easy as online shopping, offering express delivery and flexible credit terms, with quality control and logistics managed. Nivoda supports retailers with tools to showcase a wide variety of stones, reducing inventory risk while allowing businesses to remain competitive and maintain high margins. Their offerings include in-store and online solutions, such as virtual showrooms and diamond feeds, enabling retailers to instantly expand their product offerings.

📋 Description

• Build and operate search infrastructure to power ranking and multi-modal search across Nivoda’s marketplace • Design multi-tenant, configurable ranking and recommendation systems for Nivoda’s marketplace and individually branded jeweller storefronts • Build and improve contextual search and a planned conversational assistant using prompt design and retrieval-augmented approaches • Build image-to-attribute and image-to-product-match pipelines using image embeddings • Design recovery paths and confirmation steps for probabilistic systems before high-stakes actions • Define and run search- and ranking-specific evaluations, including offline ranking metrics and interleaving experiments • Evaluate and stress-test foundation model and LLM output • Own the full lifecycle of ranking and recommendation models, from features and training through evaluation, deployment, and monitoring • Design and optimize low-latency, real-time model-serving systems under production load • Use AI coding agents to build ML infrastructure and pipelines with rigorous evaluation harnesses • Work in the Discovery Pod building ranking, recommendations, search input, contextual search, conversational search, and image-upload search for a global jewellery marketplace

🎯 Requirements

• 5–10 years of experience • Information retrieval infrastructure experience with Elasticsearch/OpenSearch, Vespa, or vector-search databases such as pgvector, Pinecone, or Weaviate • Applied ML experience for ranking and recommendations, including learning-to-rank, embedding-based retrieval, and collaborative filtering • Experience owning features, training, evaluation, deployment, and monitoring of ML models • Production NLP and LLM application experience, including prompt design, retrieval-augmented approaches, and handling zero-result and tradeoff scenarios • Low-latency serving experience with real-time model-serving systems under production load • Search and ranking evaluation skills, including offline ranking metrics and interleaving experiments • Hands-on experience with foundation models and LLMs, including evaluating and stress-testing model output • Experience designing graceful failure handling for probabilistic systems • Comfort using AI coding agents to build ML infrastructure and pipelines, with strong evaluation and testing discipline • CV in English • Nice to have: computer vision fundamentals and image embeddings • Nice to have: multi-tenant configurable system design experience • Nice to have: conversational or assistant-style search product experience • Nice to have: marketplace or e-commerce search, ranking, or recommendations experience

🏖️ Benefits

• Flexible working hours • Remote-first culture • Real opportunities for growth and learning • Unlimited holiday allowance • Opportunity to join during an exponential expansion phase