Senior AI/ML Engineer

Role overview Build and operate the search, ranking, and recommendation systems that help buyers find relevant products across a large marketplace and independently branded storefronts. This is a senior, hands-on applied machine learning role spanning information retrieval, language model applications, and image-based search, with ownership from model design and training through production evaluation and monitoring.

Responsibilities - Develop and run search infrastructure for ranking and multimodal discovery, using technologies such as OpenSearch, Elasticsearch, Vespa, or vector search systems. - Build end-to-end ranking and recommendation models, including embedding retrieval and learning-to-rank, and manage their features, deployment, and monitoring. - Design configurable, multi-tenant search and ranking so storefronts can vary their experience without separate codebases. - Create contextual and conversational search using language models and retrieval-augmented methods; handle empty results and ambiguous tradeoffs carefully. - Develop image-based discovery pipelines that match uploaded photos to product attributes or catalog items. - Evaluate search quality with ranking metrics and experiments, and optimize model serving for low latency under production load.

Requirements - 5–10 years of relevant experience, including building or operating production information retrieval systems. - Applied machine learning experience with ranking and recommendations, owning the work from features and training through evaluation and operations. - Production experience with language model applications, including prompt design and retrieval-augmented approaches. - Experience building and optimizing real-time model-serving systems for production traffic. - Ability to assess ranking quality using offline metrics and methods such as interleaving experiments. - Sound judgment about probabilistic systems: test model outputs, recognize failure modes, and design graceful behavior when results are uncertain or absent.

Nice to have - Computer vision experience, especially image embeddings and image-to-product matching. - Experience with configurable systems serving multiple tenants, conversational search, or search and recommendations for a marketplace or online retail business. - Familiarity with AI coding agents, paired with disciplined evaluation and testing.

Benefits and work setup - Remote-first work with flexible hours. - Unlimited holiday allowance and opportunities for learning and career growth.