Product Manager, Search and Embeddings Job at Cohere (New York)

New

Director of Product, Search & Discovery

We are building a new Search & Discovery product organization at Scribd.com, and...

Location

United States; Canada; Mexico , San Francisco; Atlanta; Austin; Boston; Chicago; Dallas; Denver; Houston; Jacksonville; Los Angeles; Miami; New York City; Phoenix; Portland; Sacramento; Salt Lake City; San Diego; Seattle; Washington, D.C.; Ottawa; Toronto; Vancouver; Mexico City

Salary:

142500.00 - 275000.00 USD / Year

Scribd

Expiration Date

Until further notice

Requirements

10+ years of product management experience
5+ years managing PM teams or leading multi-disciplinary product groups
Demonstrated success owning discovery, personalization, search, or ranking experiences at scale in a consumer technology environment
Deep technical fluency in modern ML and AI systems, including retrieval and ranking, semantic embeddings, LLMs, retrieval augmented generation, feature stores, model evaluation, and real-time personalization
A strong track record of translating user needs, data insights, and competitive trends into breakthrough discovery features, ideally including ML or LLM powered experiences
Proven ability to lead through ambiguity, make strategic tradeoffs, and balance long-term platform investments with near-term business results
Exceptional written, visual, and verbal communication skills, including experience presenting to executives and cross-functional partners
Experience running large-scale A/B tests, user research, and multi-surface experimentation programs
Bachelor’s degree in a technical or related field (Computer Science, Engineering, Mathematics, HCI) or equivalent experience

Job Responsibility

Set the multi-year Discovery strategy
Define and drive the long-term vision for Scribd’s discovery ecosystem, including recommendations, search, ranking, and semantic content understanding
Articulate how we move from document-level retrieval to knowledge-level discovery using foundational models and LLMs
Align this vision with company priorities in engagement, retention, and subscription growth, balancing foundational ML investments with high-impact product improvements
Lead and grow a world-class product organization
Serve as the founding product leader for the Search & Discovery group, managing, mentoring, and inspiring a team of product managers across discovery surfaces and platforms
Recruit and develop top PM talent, set a high bar for product craft, and build a culture that combines deep technical curiosity with strong user empathy
Establish durable cross-functional operating rhythms with Engineering, ML, Data Science, Design, Content, and Trust & Safety
Build next generation discovery systems using LLMs and ML
Oversee the evolution of Scribd’s personalization and retrieval stack, combining semantic embeddings, behavioral signals, hybrid retrieval, and LLM-powered reasoning

What we offer

Healthcare Insurance Coverage (Medical/Dental/Vision): 100% paid for employees
12 weeks paid parental leave
Short-term/long-term disability plans
401k/RSP matching
Onboarding stipend for home office peripherals + accessories
Learning & Development allowance
Learning & Development programs
Quarterly stipend for Wellness, WiFi, etc.
Mental Health support & resources
Free subscription to the Scribd Inc. suite of products

Fulltime

Staff Product Manager, Search

In this pivotal role, you will set the strategic vision for Coursera's search ex...

Location

United States

Salary:

148200.00 - 216600.00 USD / Year

Coursera

Expiration Date

Until further notice

Requirements

Experience building consumer products at scale—ideally high-intent search, discovery, or marketplace experiences—with a strong understanding of intuitive, trustworthy UX and backend search capabilities
5+ years of product management experience owning the success of consumer-facing products, including responsibility for driving engagement and revenue outcomes
2+ years of hands-on PM experience with search, personalization, or recommendation systems, including platform-level capabilities that support multiple use cases
Proven ability to deliver complex, high-impact product initiatives from ideation through launch, using both quantitative (A/B and multivariate testing) and qualitative research to inform decisions
Demonstrated strength in influencing and inspiring cross-functional partners through clear communication, collaboration, and shared vision

Job Responsibility

Set the vision for next-generation discovery and search experiences that help learners find the right content through highly relevant, personalized, and AI-driven experiences
Own conversational search across Coursera, partnering with cross-functional product teams to deliver a seamless, end-to-end AI experience throughout the learner journey
Improve search relevance and quality by leveraging advances in IR/ML, embeddings, and LLMs to enhance query understanding, semantic and multilingual search, and personalized ranking
Drive rapid experimentation to understand evolving learner behaviors, market trends, and growth opportunities, using data to inform strategy and product decisions
Leverage market insights and competitive analysis to identify opportunities for revenue growth and differentiated personalization across the platform
Define, track, and optimize KPIs related to discovery, conversion, and merchandising, collaborating closely with Marketing and Product partners to align with business and revenue goals

What we offer

competitive, zone-based pay aligned to your location, experience, and role level
comprehensive health and wellness benefits
bonus and RSU equity programs
global perks designed to help you grow and thrive wherever you are

Fulltime

New

Senior Product Manager, Data & Retrieval

Harvey is building the AI platform for the world’s top legal and professional se...

Location

United States , San Francisco

Salary:

178500.00 - 241500.00 USD / Year

Harvey

Expiration Date

Until further notice

Requirements

5+ years of experience building or managing search, retrieval, recommendation, or data platforms at scale
Experience working with complex, heterogeneous, or domain-specific datasets with structured + unstructured data
Understanding of modern retrieval methods, including hybrid search (lexical + vector), dense retrieval, re-ranking, embeddings, chunking strategies, and index optimization
Hands-on experience with LLMs or RAG frameworks (evaluation, grounding, hybrid pipelines, query rewriting, LLM-as-a-judge, retrieval metrics)
Ability to partner with engineers on technical architecture, with enough depth to challenge assumptions, propose solutions, and influence design
A product mindset for search—balancing user needs, domain complexity, and system constraints to propose high-leverage improvements

Job Responsibility

Drive the roadmap and strategy for Harvey’s “Data Factory”, ensuring we scale our data 100x through new platforms that build the ‘legal index’ of the world
Work with internal operations and external data providers to methodically expand coverage, accelerate execution, and improve dataset quality
Own and evolve Harvey’s end-to-end data architecture—from ingestion and transformation to storage, indexing, and retrieval—ensuring performance, reliability, and scalability for LLM-powered products
Partner with Applied AI engineers to build and optimize retrieval systems, embeddings, search models, and evaluation frameworks
Architect and oversee large-scale ingestion pipelines that aggregate, normalize, and continuously update millions of heterogeneous legal documents across global jurisdictions
Collaborate cross-functionally with Product Engineering, Applied AI, Research, and Platform teams to deliver high-quality production systems that support reasoning, summarization, and legal research workflows

What we offer

Comprehensive health, dental and vision coverage
retirement benefits (401k match up to 4%)
flexible PTO
equity plan
bonus

Fulltime

Senior Machine Learning Engineer, Personalization and Recommendations

As a Senior Machine Learning Engineer on the Personalization & Recommendations t...

Location

United States , San Francisco

Salary:

183360.00 - 248000.00 USD / Year

EdTech Jobs

Expiration Date

Until further notice

Requirements

5+ years of experience in applied machine learning or ML-heavy software engineering, with a strong focus on personalization, ranking, or recommendation systems
Demonstrated impact improving key metrics such as CTR, retention, or engagement through recommender or search systems in production
Strong hands-on skills in Python and PyTorch, with expertise in data and feature engineering, distributed training and inference on GPUs, and familiarity with modern MLOps practices — including model registries, feature stores, monitoring, and drift detection
Deep understanding of retrieval and ranking architectures, such as Two-Tower models, deep cross networks, Transformers, or MMoE, and the ability to apply them to real-world problems
Experience with large-scale embedding models and vector search, including FAISS, ScaNN, or similar systems
Proficiency in experiment design and evaluation, connecting offline metrics (AUC, NDCG, calibration) with online A/B test outcomes to drive product decisions
Clear, effective communication, collaborating well with product managers, data scientists, engineers, and cross-functional partners
A growth and mentorship mindset, helping elevate team quality in modeling, experimentation, and reliability
Commitment to responsible and inclusive personalization, ensuring our systems respect learner privacy, fairness, and diverse goals

Job Responsibility

Design and implement personalization models across candidate retrieval, ranking, and post-ranking layers, leveraging user embeddings, contextual signals and content features
Develop scalable retrieval and serving systems using architectures such as Two-Tower models, deep ranking networks, and ANN-based vector search for real-time personalization
Build and maintain model training, evaluation, and deployment pipelines, ensuring reliability, training–serving consistency, observability, and robust monitoring
Partner with Product and Data Science to translate learner objectives (engagement, retention, mastery) into measurable modeling goals and experiment designs
Advance evaluation methodologies, contributing to offline metric design (e.g., NDCG, CTR, calibration) and supporting rigorous A/B testing to measure learner and business impact
Collaborate with platform and infrastructure teams to optimize distributed training, inference latency, and serving cost in production environments
Stay informed on industry and research trends, evaluating opportunities to meaningfully apply them within Quizlet’s ecosystem
Mentor junior and mid-level engineers, supporting technical growth, experimentation rigor, and responsible ML practices
Champion collaboration, inclusion, curiosity, and data-driven problem solving, contributing to a healthy and productive team culture

What we offer

20 vacation days
Competitive health, dental, and vision insurance (100% employee and 75% dependent PPO, Dental, VSP Choice)
Employer-sponsored 401k plan with company match
Access to LinkedIn Learning and other resources to support professional growth
Paid Family Leave, FSA, HSA, Commuter benefits, and Wellness benefits
40 hours of annual paid time off to participate in volunteer programs of choice

Fulltime

Principal AI Engineer

We are looking for a Principal AI Engineer to lead the design and deployment of ...

Location

United States

Salary:

200000.00 - 300000.00 USD / Year

Apollo.io

Expiration Date

Until further notice

Requirements

10+ years of software engineering experience
at least 3 years in applied LLM or agentic AI systems (2023–present)
proven success in deploying LLM-powered products used by real users at scale
deep backend & systems engineering expertise with Python, distributed systems, and scalable APIs
familiarity with LangChain, LlamaIndex, or similar orchestration frameworks
experience with RAG pipelines, vector DBs, embedding models, and semantic search tuning
experience managing performance across cloud providers (e.g., AWS Bedrock, OpenAI, Anthropic, etc.)
demonstrated experience building multi-step agents, planning workflows, chaining reasoning steps, and integrating APIs with agent memory/state
comfort with advanced prompting strategies, few-shot and chain-of-thought reasoning, and embedding retrieval setups
strong understanding of AI system evaluation, human ratings, A/B experimentation, and feedback loop pipelines

Job Responsibility

Architect and lead the development of multi-agent systems capable of long-horizon planning, reasoning, and API orchestration
build reusable agentic components that integrate deeply into sales and marketing processes
own and evolve our in-house platform for scalable, low-latency, and cost-efficient LLM and agent deployments
lead design of interfaces powered by natural language understanding and retrieval-augmented generation (RAG)
build embedding-based, intent-aware search and personalization systems tuned to business user needs
drive innovation in personalized outreach generation using context-aware generation pipelines
tune inference pipelines, caching layers, and model selection logic for high-scale, cost-aware performance
define and drive robust offline and online testing methodologies (A/B, sandboxing, human evals) across agents and LLM flows
architect human-in-the-loop systems and telemetry to improve accuracy, UX, and explainability over time

What we offer

equity
company bonus or sales commissions/bonuses
401(k) plan
at least 10 paid holidays per year
flex PTO
parental leave
employee assistance program
wellbeing benefits
global travel coverage
life/AD&D/STD/LTD insurance

Fulltime

Staff AI Context Engineer

MagicSchool is seeking a Staff AI Context Engineer to architect and enhance the ...

Location

United States

Salary:

205000.00 - 240000.00 USD / Year

EdTech Jobs

Expiration Date

Until further notice

Requirements

Deep Knowledge Systems Experience: 5+ years building large-scale information systems with at least 2+ years in staff/senior roles. Extensive hands-on experience with RAG systems, knowledge graphs, or semantic search platforms in production environments.
Graph Database Expertise: Deep experience with graph databases (Neo4j, Neptune, or similar), including schema design, query optimization (Cypher, Gremlin), and building graph-based applications.
RAG & Retrieval Mastery: Demonstrated expertise building production RAG systems including embedding selection, chunking strategies, hybrid search, reranking, and retrieval evaluation. Familiarity with vector databases (pgvector, Pinecone, Weaviate, Qdrant).
Embedding & NLP Background: Strong understanding of embedding models (sentence transformers, domain-specific embeddings), fine-tuning approaches, and semantic similarity. Experience with document processing, entity extraction, and text chunking for optimal retrieval.
Technical Stack: Strong coding skills in Python and/or TypeScript/Node.js. Experience with our stack (TypeScript, Node.js, PostgreSQL, NextJS, Supabase) plus graph databases and vector stores. Familiarity with LLM APIs and context management patterns.
Information Architecture: Deep understanding of information retrieval theory, semantic search, knowledge representation, and strategies for organizing complex domain knowledge for both human and AI consumption.
Leadership & Impact: Track record of architecting complex knowledge systems, making high-leverage technical decisions about information architecture, and mentoring engineers on sophisticated retrieval and graph concepts.

Job Responsibility

Knowledge Graph & Semantic Architecture: Architect and implement graph-based knowledge systems (Neo4j, Neptune, etc) that represent educational content relationships, standards alignments, prerequisite chains, curriculum coherence, learning progressions, and pedagogical connections.
Graph Schema & Ontology Development: Design and evolve ontologies and schemas for educational content, defining entity types (standards, concepts, skills, assessments), relationship semantics, and property models.
GraphRAG Implementation: Build GraphRAG systems that combine knowledge graph traversal with vector similarity, enabling agents to retrieve contextually connected educational materials.
Retrieval Pipeline Architecture: Architect and implement sophisticated retrieval-augmented generation pipelines including hybrid search (dense + sparse), multi-stage retrieval, reranking strategies, and query understanding.
Embedding & Vectorization Strategy: Design and operationalize embedding pipelines for educational content, selecting and fine-tuning embedding models, implementing chunking strategies, and managing vector stores at scale.
Retrieval Evaluation & Optimization: Design evaluation pipelines that measure retrieval precision, recall, MRR, and NDCG across educational content types. Continuously optimize retrieval quality.
Document Ingestion & Processing: Build robust ingestion systems that process structured and unstructured educational content, extracting entities, relationships, and metadata for knowledge base population.
Semantic Parsing & Extraction: Implement NLP pipelines for educational content that extract key concepts, prerequisite relationships, learning objectives, and pedagogical metadata.
Memory & Context Management: Invent and operationalize memory compaction mechanisms, session state management, and cross-conversation memory patterns that allow agents to maintain coherence across extended teaching workflows.
Context Evaluation & Monitoring: Design evaluation frameworks that measure retrieval precision, token relevance, attention allocation, and reasoning coherence as context evolves across sessions.

What we offer

Flexibility of working from home.
Unlimited time off.
Choice of employer-paid health insurance plans. Dental and vision are also offered at very low premiums.
Generous stock options, vested over 4 years.
401k match.
Monthly wellness stipend.

Fulltime

New

Data Engineer

Join us at Seismic, a cutting-edge technology company leading the way in the Saa...

Location

India , Hyderabad

Salary:

Not provided

Seismic

Expiration Date

Until further notice

Requirements

2+ years of professional experience in data engineering or a backend-heavy software engineering role
Expert-level Python coding skills
Deep, hands-on experience with LangChain or LangGraph to build sophisticated multi-step chains and agentic systems
Proven experience implementing and tuning Vector Databases for high-volume RAG pipelines
Strong understanding of traditional data modeling, ETL/ELT processes, and working with SQL/NoSQL databases
Solid grasp of embedding models, tokenization, and modern information retrieval techniques
Thrive in fast-paced environments and enjoy staying updated with the rapidly evolving landscape of GenAI and search technologies

Job Responsibility

Architect AI Data Pipelines: Design and maintain robust data ingestion and transformation pipelines tailored for LLM training, fine-tuning, and Retrieval-Augmented Generation (RAG)
Build Agentic Workflows: Utilize LangGraph to develop complex, state-managed AI agents and cyclical workflows that enhance automated user interactions
Optimize RAG Systems: Architect the retrieval layer of our AI applications, implementing efficient document embedding strategies and semantic search
Manage Vector Infrastructure: Implement and optimize Vector Databases (e.g., Pinecone, Weaviate, or Milvus) to ensure high-performance data retrieval and storage
Scale Data Models: Create scalable data schemas that support both structured and unstructured data, ensuring seamless integration with our AI services
Performance Engineering: Identify and resolve latency bottlenecks in data retrieval and embedding generation to ensure real-time AI responsiveness
Collaborate Cross-Functionally: Partner with AI Researchers and Product Managers to transition experimental AI prototypes into production-ready data products

Fulltime

Sr. Software Development Engineer

You will safeguard the quality of our AI and GenAI features by evaluating model ...

Location

India , Hyderabad

Salary:

Not provided

Highspot

Expiration Date

Until further notice

Requirements

4+ years of experience as a Software Development Engineer in AI/ML systems
Strong coding skills in Python (evaluation pipelines, data processing, metrics computation)
Hands-on experience with evaluation frameworks (Ragas or equivalent)
Knowledge of vector embeddings, similarity search, and RAG evaluation
Familiarity with evaluation metrics (precision, recall, F1, relevance, hallucination detection)
Understanding of LLM-as-a-judge evaluation approaches
Strong analytical and problem-solving skills
ability to combine human judgment with automated evaluations
Bachelor’s or Master’s degree in Computer Science, Data Science, or related field
Strong English written and verbal communication skills

Job Responsibility

Evaluation Frameworks – Develop reusable, automated evaluation pipelines using frameworks such as Raagas
integrate LLM-as-a-judge methods for scalable assessments
Golden Datasets – Build and maintain high-quality benchmark datasets in collaboration with subject matter experts
AI Output Validation – Evaluate results across text, documents, audio, and video, using both automated metrics and human-in-the-loop judgment
Metric Evaluation – Implement and track metrics such as precision, recall, F1 score, relevance scoring, and hallucination penalties
RAG & Embeddings – Design and evaluate retrieval-augmented generation (RAG) pipelines, vector embedding similarity, and semantic search quality
Error & Bias Analysis – Investigate recurring errors, biases, and inconsistencies in model outputs
propose solutions
Framework & Tooling Development – Build tools that enable large-scale model evaluation across hundreds of AI agents
Cross-Functional Collaboration – Partner with ML engineers, product managers, and QA peers to integrate evaluation frameworks into product pipelines

Fulltime

Product Manager, Search and Embeddings

Cohere

Location:
United States; Canada , New York ▼
Toronto

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Additional Information:

Job Posted:
February 20, 2026

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