[Hiring] Senior AI/ML Engineer @Nivoda

Role Description

We're hiring a Senior AI/ML Engineer for the Discovery Pod to help build and run the ranking, recommendation, and search systems buyers rely on to find the right stone or piece in seconds. This is real information retrieval and applied ML work on production infrastructure — search systems, embedding-based retrieval, learning-to-rank, LLM-powered contextual and conversational search, image embeddings for photo-based search — not configuring a hosted search widget or calling a model API and moving on. You'll own models end to end, from features and training through evaluation, deployment, and monitoring, and you'll be expected to understand how these probabilistic systems behave and fail, because that understanding is the job, not an adjacent skill.

Qualifications

• 5-10 years of experience
• Information retrieval infrastructure experience — building or operating real search systems (Elasticsearch/OpenSearch, Vespa, or vector-search databases like pgvector, Pinecone, or Weaviate)
• Applied ML for ranking and recommendations, end to end — learning-to-rank, embedding-based retrieval, collaborative filtering
• NLP and LLM application experience — production experience building on top of language models, including prompt design, retrieval-augmented approaches
• Low-latency serving experience — you've built and optimized real-time model-serving systems under production load
• Specialized evaluation skills for search and ranking quality — offline ranking metrics, interleaving experiments
• Direct, hands-on experience building with foundation models and LLMs as an engineering material
• Experience designing for graceful failure in probabilistic systems
• Comfort using AI coding agents to build ML infrastructure and pipelines

Requirements

• Build and operate real search infrastructure — Elasticsearch/OpenSearch, Vespa, or vector-search databases
• Design multi-tenant, configurable ranking and recommendation systems
• Build and improve Contextual Search and our planned conversational assistant
• Build image-to-attribute and image-to-product-match pipelines
• Define and run search- and ranking-specific evaluation
• Own the full lifecycle of ranking and recommendation models
• Design and optimize low-latency, real-time model-serving systems
• Use AI coding agents to build ML infrastructure and pipelines

Benefits

• Flexible working hours and a remote-first culture
• Real opportunities for growth and learning
• Unlimited holiday allowance
• The chance to join during an exponential expansion phase

Company Description

Nivoda is the operating system for the global jewellery industry. We connect diamond and gemstone suppliers directly with jewellery retailers across more than 70 countries, replacing a slow, offline, relationship-gated way of trading with a single digital marketplace. We're already powering over $300M in annual transactions, inside an industry worth more than $350B globally — and we're still early.

Our mission is to make buying and selling diamonds and gemstones radically simpler, everywhere in the world.