Innodata Sr Language Data Scientist – Search Specialization

Who We Are

Innodata (NASDAQ: INOD) is a leading data engineering company. With more than 2,000 customers and operations in 13 cities around the world, we are the AI technology solutions provider‑of‑choice to 4 out of 5 of the world’s biggest technology companies, as well as leading companies across financial services, insurance, technology, law, and medicine.

Innodata is building a team of Language Data Scientists and Gen AI experts to help our customers advance search and information retrieval applications powered by GenAI. You will work hands‑on with search‑specific datasets (queries, documents, relevance judgments) in multi‑modal and multilingual environments, collaborating with cross‑functional partners including search engineers and product teams. You will leverage your expertise in query understanding, semantic matching, and ranking systems alongside human and synthetic data workflows to drive innovation in search relevance and user experience.

• You have at least 5 years of relevant experience with data creation, curation, and analysis for search and information retrieval systems, including work with GenAI applications (e.g. neural ranking, semantic search, query understanding, RAG‑enhanced search, multi‑stage ranking pipelines).
• Experience spans creating and annotating search datasets—from query‑document pairs to relevance judgments, and query intent classifications.
• You have demonstrated success working on search product challenges such as relevance optimization, query intent understanding, or improving search result diversity and freshness.
• Understand the unique data annotation challenges in search (inter‑rater disagreement on relevance, context‑dependent query understanding, geographic and temporal relevance).
• You are experienced driving long term projects where you set the strategic plan towards success, using your knowledge of AI, data science, and process design excellence.
• You are an expert at working cross‑functionally with both technical and non‑technical stakeholders. Despite ambiguity, you use your technical knowledge and experience of working with multiple stakeholders to drive solutions.
• You bring a research‑oriented mindset towards developing long‑term excellence in search systems.
• You are an expert in designing collection, evaluation and quality assurance processes for search data, using human‑in‑the‑loop and synthetic techniques.
• Understand search‑specific evaluation metrics and quality frameworks, and you can design human relevance judging workflows that account for query ambiguity and subtlety.
• Your understanding of machine learning, Large Language Models (LLMs), and Retrieval‑Augmented Generation (RAG), neural ranking architectures, and dense retrieval methods help you tackle search and information retrieval challenges with a critical, innovative mindset.
• You can assess how GenAI techniques improve search relevance, ranking, and user experience.

As a Senior Language Data Scientist, you lead projects and own processes for optimizing search and retrieval systems by creating, validating and annotating search‑specific data for LLM/ML applications. This includes query‑document pairs, relevance judgments, query intent labels, search result quality assessments, and multimodal search scenarios (image search, product search, news search). You work across different search domains—from web search to e‑commerce to vertical search.

You consult and engage with customers to understand their business goals and design processes to meet them. You generate insights about the client’s processes and products to drive improvement and innovation. You advise and support business unit heads on engaging with customers to understand the upstream activities that would be performed using Innodata Inc services.

• You can lead long‑term projects with high complexity and ambiguity from first discussion with the client to completion.
• Design/improve workflows to create data for AI/ML training and evaluation. Includes human annotation and data‑collection workflows, as well as synthetic ones.
• Design and refine search data annotation frameworks, including…