embedding models Jobs

The Voyage AI team at MongoDB is building state-of-the-art embedding models and rerankers for efficient unstructured data search and retrieval, crucial for RAG, recommendation systems, and semantic search. This team, comprised of AI researchers from top universities, was recently acquired by MongoDB and is integrating its advanced embedding models with MongoDB's data platform to create powerful end-to-end solutions. We are seeking a Senior Research Scientist to join this dynamic team and contribute to the development of next-generation AI models, tackling complex challenges at the intersection of machine learning research and the practical deployment of large neural networks.

$101k - $273k

The Voyage AI team at MongoDB is building state-of-the-art embedding models and rerankers for accurate and efficient unstructured data search and retrieval, crucial for RAG, recommendation systems, and semantic search. This team, comprised of AI researchers from top universities, was recently acquired by MongoDB and is integrating its advanced embedding models with MongoDB's data platform to create powerful end-to-end solutions. We are seeking a Staff Research Scientist to contribute to the development of next-generation AI models, tackling complex challenges at the intersection of machine learning research and the practical deployment of large neural networks.

$151k - $297k

Plaid is at the forefront of transforming the financial industry through AI. As a founding member of the newly formed AI Applications Team, you will play a pivotal role in scaling successful AI initiatives and accelerating Plaid's evolution into an AI-first company. This role offers the unique opportunity to lead projects that enable and scale our business with major AI customers and partners, starting with personal finance use cases and expanding into diverse areas. You will be instrumental in defining the future of AI in FinTech, from how consumers manage their finances to how developers build applications.

$265k - $370k

Plaid is at the forefront of revolutionizing the FinTech industry through AI. We are building the tools and experiences that empower developers and consumers to interact with financial data in new ways. As AI drives a significant paradigm shift, Plaid is uniquely positioned to be the financial data backbone for AI applications. We are looking for a leader to join our newly formed AI Applications Team, dedicated to scaling our successful AI initiatives and accelerating Plaid's transformation into an AI-first company. This role offers a unique opportunity to shape the future of AI in FinTech and influence industry developments.

$238k - $362k

Exa is an applied AI lab building a revolutionary search engine. We develop massive-scale infrastructure to crawl the web, train state-of-the-art embedding models, and design high-performance vector databases. Our goal is to create perfect search over all the world's information, surpassing current capabilities. As a Software Engineer on Knowledge Systems, you will contribute to building systems that understand and reason over knowledge from the web and beyond, enabling AI agents to answer questions with exceptional precision and completeness.

$180k - $350k

Parallel is seeking a researcher who thinks like an engineer, or an engineer who thinks like a researcher, to join our team. You will design and train the models that power Parallel's APIs, focusing on the intelligence layer that helps AI agents find exactly what they need from the open web. This role involves tackling research problems at hyperscale, such as training embedding models that capture semantic intent, balancing model expressiveness with sub-second retrieval latency, and maintaining index freshness. You will be building information retrieval systems reimagined for the LLM era, combining classical IR techniques with modern deep learning at a scale that demands new solutions.

$150k - $300k

Exa is an applied AI lab building a revolutionary search engine. We develop massive-scale infrastructure to crawl the web, train state-of-the-art embedding models, and design high-performance vector databases. Our goal is to create perfect search over all the world's information, surpassing current capabilities. This role is for an ML Research Engineer focused on training embedding models for this mission, involving the design of novel transformer-based search architectures, dataset creation, evaluation, and continuous improvement.

$180k - $350k