11 days ago

Product Manager, Search and Embeddings

Cohere

On Site
Full Time
$180,000
New York, NY

Job Overview

Job TitleProduct Manager, Search and Embeddings
Job TypeFull Time
CategoryCommerce
Experience5 Years
DegreeMaster
Offered Salary$180,000
LocationNew York, NY

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Job Description

Who are we?

Our mission at Cohere is to scale intelligence to serve humanity. We are training and deploying frontier models for developers and enterprises building AI systems for magical experiences like content generation, semantic search, RAG, and agents. We believe our work is instrumental to the widespread adoption of AI.

We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what’s best for our customers.

Cohere is a team of researchers, engineers, designers, and more, all passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.

Join us on our mission and shape the future!

Product Management At Cohere

Our team is responsible for driving Cohere’s technology direction to the world through our interfaces. We’ve released generative models like Command A, Retrieval models like Embed 4 and Rerank 3.5, and products such as North and Compass. At Cohere, Product Managers work on core models, APIs, and end-to-end products that serve our enterprises and developers.

We view the role that PMs play at Cohere to be “full-stack,” meaning you will work with cross-functional stakeholders at every step of the way when training and evaluating models, delivering products, ensuring successful go-to-market, and achieving customer happiness.

About The Search And Embeddings Role

One of the most exciting applications for generative AI is in its use in Retrieval Augmented Generation (RAG) and Agents – Search and Embeddings plays a critical role in ensuring that Large Language Models (LLMs) have the correct context to answer user needs. The focus of this Product Manager, Search and Embeddings will not only be on the role that search plays in RAG/Agents but also in traditional search. The expectation is that you have experience working on Search products and Embedding / Cross-Encoder models.

The Product Manager, Search and Embeddings manages 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

In This Role, You Will

  • 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 State-Of-The-Art (SOTA).

In order to be successful in this role, you have:

  • 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 Computer Science (CS), Machine Learning (ML), or a related field, or have 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.
  • Showcase strong leadership, organizational, and execution skills, along with proven communication abilities.

If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply!

We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.

Full-Time Employees At Cohere Enjoy These Perks

  • 🤝 An open and inclusive culture and work environment
  • 🧑‍💻 Work closely with a team on the cutting edge of AI research
  • 🍽 Weekly lunch stipend, in-office lunches & snacks
  • 🦷 Full health and dental benefits, including a separate budget to take care of your mental health
  • 🐣 100% Parental Leave top-up for up to 6 months
  • 🎨 Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement
  • 🏙 Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend
  • ✈️ 6 weeks of vacation (30 working days!)

Key skills/competency

  • Retrieval Augmented Generation
  • RAG
  • Embeddings
  • Rerank
  • Search Products
  • Machine Learning
  • Product Strategy
  • API Development
  • Data-driven Decisions
  • Cross-functional Collaboration

Tags:

Product Manager
Search
Embeddings
Rerank
Retrieval Augmented Generation
RAG
Product Strategy
AI
Machine Learning
Go-to-Market
Embeddings
Cross-Encoder models
APIs
LLMs
Algorithms
Large Scale Systems
Statistics
Retrieval
Generative AI

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How to Get Hired at Cohere

  • Research Cohere's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
  • Tailor your resume: Highlight experience with search products, embedding models, and RAG in an AI/ML context.
  • Showcase technical depth: Emphasize background in machine learning, algorithms, and large-scale systems.
  • Prepare for product strategy questions: Demonstrate your ability to define roadmaps and drive monetization in competitive AI landscapes.
  • Highlight collaboration skills: Provide examples of working effectively with cross-functional teams in technical environments.

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