Product Manager, Search and Embeddings at Cohere

New York, New York, United States

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, TechnologyIndustries

Requirements

At least 4+ years of product management experience, understanding customer needs, and launching successful products
At least 1+ years of working on search products and embedding/reranking models
Obtained a Bachelor’s or postgrad degree in CS, ML or related field, or a background in machine learning, algorithms, large scale systems, and statistics
Proven experience working in a technical environment with cross-functional teams to drive product vision, define requirements, and guide the team through key milestones
Strong leadership, organizational, and execution skills, along with proven communication abilities

Responsibilities

Define strategic priorities and roadmap for improving retrieval model performance, focusing on enterprise needs and emerging capabilities
Use data and customer engagements to better understand user needs and guide future product and model development
Collaborate with a wide range of stakeholders, including teams in product, finance, go-to-market, engineering, and marketing
Drive product strategy and monetization through a deep understanding of the increasingly dynamic and competitive AI Landscape
Read lots of papers and collaborate with ML on ensuring our models remain SOTA
Manage the following models and products: Embeddings (Embed-v4.0), Rerank (Rerank-v3.5), Compass (Cohere’s Search Solution)
Evaluation of Search performance across all products and models

Skills

Product Management

RAG

Embeddings

Semantic Search

Agents

LLMs

APIs

GTM

Retrieval Models

Cohere

Provides NLP tools and LLMs via API

About Cohere

Cohere provides advanced Natural Language Processing (NLP) tools and Large Language Models (LLMs) through a user-friendly API. Their services cater to a wide range of clients, including businesses that want to improve their content generation, summarization, and search functions. Cohere's business model focuses on offering scalable and affordable generative AI tools, generating revenue by granting API access to pre-trained models that can handle tasks like text classification, sentiment analysis, and semantic search in multiple languages. The platform is customizable, enabling businesses to create smarter and faster solutions. With multilingual support, Cohere effectively addresses language barriers, making it suitable for international use.

Toronto, CanadaHeadquarters

2019Year Founded

$914.4MTotal Funding

SERIES_DCompany Stage

AI & Machine LearningIndustries

501-1,000Employees

Risks

Competitors like Google and Microsoft may overshadow Cohere with seamless enterprise system integration.

Reliance on Nvidia chips poses risks if supply chain issues arise or strategic focus shifts.

High cost of AI data center could strain financial resources if government funding is delayed.

Differentiation

Cohere's North platform outperforms Microsoft Copilot and Google Vertex AI in enterprise functions.

Rerank 3.5 model processes queries in over 100 languages, enhancing multilingual search capabilities.

Command R7B model excels in RAG, math, and coding, outperforming competitors like Google's Gemma.

Upsides

Cohere's AI data center project positions it as a key player in Canadian AI.

North platform offers secure AI deployment for regulated industries, enhancing privacy-focused enterprise solutions.

Cohere's multilingual support breaks language barriers, expanding its global market reach.

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