Contextual AI Research Engineer Job at Meta (Sunnyvale)

Research Engineer - Contextual AI

In this role, you will adapt and deploy advanced real-time smart glasses algorit...

Location

United States , Redmond

Salary:

181000.00 USD / Year ▼

Meta

Expiration Date

Until further notice

Requirements

Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta
Master's degree in Computer Engineering, Computer Science, or Electrical Engineering and Computer Sciences or equivalent practical experience
4+ years of experience working in large scale C++ and Python code base
4+ years of experience in developing and prototyping machine perception
Experience in implementing computer vision algorithms for efficient execution on embedded systems
Demonstrated examples of delivering an end-to-end system rather than a single component

Job Responsibility

Execute engineering development to advance the state-of-the-art in machine perception research for Contextualized Al, both on-device and on back-end
Collaborate closely with researchers, engineers, and product managers across multiple teams at Meta to design, architect and implement prototypes
Debug system-level, multi-component issues that typically span across multiple layers from sensor to application

What we offer

bonus
equity
benefits

Context Layer & GTM Engineer

Bloomreach is seeking a Context Layer & Platform Engineer to architect and maint...

Location

Czechia , Bratislava; Brno; Prague

Salary:

Not provided

Bloomreach

Expiration Date

Until further notice

Requirements

You've built or scaled data pipelines, ETL systems, or API backends that serve multiple downstream consumers - and understand the discipline of versioning, backward compatibility, and operational stability
You know Salesforce deeply - data model, custom objects, field governance, deduplication strategies, API limitations - and can architect data quality processes that scale
You're expert with N8N, Supabase/Postgres, and API integrations. You can design schemas, optimize queries, version APIs, and think about performance at scale. You've built systems that balance flexibility with simplicity
You understand LLM-adjacent tooling and can reason about prompt versioning, retrieval quality, latency trade-offs, and how to structure data so agents consume it predictably
You love operational rigor - monitoring, alerting, observability, runbooks. You believe that boring infrastructure is good infrastructure, and you want to measure and communicate it
You're comfortable with ambiguity and can break down a big architectural challenge ("serve 200 agents with consistent context") into testable, shippable milestones
You thrive in cross-functional environments and can translate between data engineers, product teams, AI researchers, and business stakeholders. You can speak both technical and business language
You're driven by the challenge of turning messy data into clean intelligence - and seeing that intelligence power products and decisions in real time
You're curious about how GTM works and motivated to understand not just the "what" but the "why" - so you build systems that are useful, not just technically sound
You have strong project ownership instincts - you see things through from design to maintenance, and you take pride in systems that run reliably at scale

Job Responsibility

Own Salesforce data integrity: Take responsibility for data quality, deduplication, and enrichment across Salesforce. Use AI enriching accounts and contacts with the right data, eliminating duplicates, standardizing fields, validating data freshness, and ensuring that all context flowing through the system is reliable. You are the keeper of the single source of truth
Engineer the context retrieval backbone: Design and ship versioned, documented API endpoints that GTM agents call to retrieve context - contacts, accounts, engagement history, intent signals, enrichment data - with consistent response contracts, fast latency, and intelligent filtering/boosting/time-decay logic. These endpoints become the foundation for scaling from 10 to 200 agents
Optimize retrieval performance: Continuously tune query logic, filters, boosts, and ranking algorithms so answers are contextually relevant, fast (sub-second latency), and cost-effective. Every agent query should return signal, not noise
Scale “GTM Brain” data sources without breaking agents: Add new sources - product usage, web signals, third-party enrichment, intent platforms - to the context layer without forcing agents to rebuild their logic. Design the system so agents stay stable while context grows richer
Keep context fresh and resilient: Build and operate background jobs that refresh context on schedule, detect and fix failed re-embeddings, backfill deltas, and maintain data pipelines that feed agents with up-to-date intelligence without disruption or drift
Enable agent developers and operators: Create starter queries and templated context patterns that new agents can adopt quickly. Coordinate with the enablement and AI Ops teams to make context accessible to non-engineers
Collaborate on vendor strategy: Help evaluate, integrate, and own relationships with key vendors like N8N, Clay, Rattle - ensuring their data flows cleanly into your context architecture and meets our latency and freshness requirements
Participate in building the GTM data stack of the future: Work with RevOps, and AI Ops to understand how Salesforce, enrichment platforms, N8N, Supabase/Postgres, LLM tools, and analytics integrate - co-creating a scalable, maintainable system that can grow to support 200+ agents without technical debt

What we offer

A great deal of freedom and trust
We believe in flexible working hours
We work virtual-first with several Bloomreach Hubs available across three continents
We organize company events
We encourage and support our employees to engage in volunteering activities - every Bloomreacher can take 5 paid days off to volunteer
People Development Program -- personal development workshops
communication coach available
Leader Development Program
$1,500 professional education budget on an annual basis
Employee Assistance Program -- with counselors

Fulltime

Research Scientist Intern, Multimodal Contextual AI

At Reality Labs, our team brings novel experiences to life on Meta’s AR devices....

Location

United States , Sunnyvale

Salary:

7313.00 - 12134.00 USD / Month

Meta

Expiration Date

Until further notice

Requirements

Currently has, or is in the process of obtaining a PhD in Computer Science, Electrical Engineering, or a related field
Programming and simulation experience with languages such as C/C++ and Python
Experience with computer architecture and HW/SW co-design and co-optimization
Must obtain work authorization in the country of employment at the time of hire, and maintain on-going work authorization during employment

Job Responsibility

Build and characterize experimental HW+SW systems on AR devices and device prototypes
Develop embedded firmware and software in RTOS and mobile operating systems, e.g. AOSP
Collaborate with other researchers and engineers across various disciplines

AI Knowledge Optimization Specialist

We are seeking a detail-oriented and tech-curious AI Knowledge Optimization Spec...

Location

United States , North Olmsted

Salary:

60000.00 - 99000.00 USD / Year

Therma-Tru

Expiration Date

Until further notice

Requirements

Bachelor’s degree or 5+ years of experience working with a knowledge base or in knowledge management, technical documentation, or content operations role
Demonstrated ability to structure and optimize content for digital tools or platforms
Strong analytical and critical thinking skills with a focus on structure, logic, and clarity
Experience working with structured content, metadata, or tagging systems
Ability to research and synthesize technical best practices into actionable strategies
Excellent attention to detail and ability to follow complex formatting standards
Comfortable working independently and managing multiple priorities
Proficiency in tools such as Google Workspace, Microsoft Office, or similar

Job Responsibility

Research and apply best practices for optimizing knowledge base content for AI tools, including semantic search, chatbots, and virtual assistants
Analyze and reformat content to improve AI comprehension, retrieval accuracy, and contextual relevance
Collaborate with AI product teams and knowledge managers to define formatting, tagging, and metadata standards
Apply content structures that support natural language processing (NLP), entity recognition, and intent mapping
Test and evaluate how knowledge performs in AI environments and iterate based on findings
Document optimization strategies, formatting guidelines, and AI-readiness standards
Provide guidelines and support to knowledge management team to ensure AI consumption best practices are leveraged as new content is created
Stay informed on trends in AI, machine learning, and knowledge engineering to continuously improve content alignment

What we offer

robust health plans
a market-leading 401(k) program with a company contribution
product discounts
flexible time off benefits
adoption benefits
more
numerous ERGs (Employee Resource Groups)

Fulltime

Research Scientist Intern, Multimodal Generative AI and Robotics

The research intern will work on cutting edge research problems to innovate nove...

Location

United States , Redmond

Salary:

7650.00 - 12134.00 USD / Month

Meta

Expiration Date

Until further notice

Requirements

Currently has, or is in the process of obtaining a PhD degree in the domain of computer-vision, computer graphics, 3D machine perception or deep learning
Knowledge in deep learning, computer vision, graphics, generative modeling, LLMs and VLMs
Hands-on experience with implementing deep learning algorithms, large-scale training, benchmark and evaluation
Experience working within Python environments such as pytorch
Experience working in a Unix environment
Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment

Job Responsibility

Plan and execute cutting-edge research and development to advance the state-of-the-art in machine learning and large-scale training
Collaborate with other researchers and engineers across machine perception teams at Meta to develop experiments, prototypes, and concepts that advance the state-of-the-art contextual AI and robotic systems
Work with the team to help design, setup, and run practical experiments and prototype systems related to large-scale high-quality sensing and machine reasoning

Fulltime

New

Product Designer - Realtime AI

At Meta, we are building Personal Superintelligence to empower every individual ...

Location

United States , Menlo Park

Salary:

201000.00 - 278000.00 USD / Year

Meta

Expiration Date

Until further notice

Requirements

Advanced Craft & Systems Thinking: 8-10+ years of experience in product design or creative direction, with a portfolio showcasing the experience solving complex, systems-level problems
AI/ML Fluency: Demonstrated experience designing for non-deterministic systems. You understand prompting, model constraints, and how to design for "graceful failure" in AI
Strategic Autonomy: Proven track record of navigating extreme ambiguity and driving projects from concept to execution with minimal guidance
Prototyping: Proficiency in Figma and a high degree of experience with AI-assisted coding or prototyping tools (e.g., Cursor, Framer, or similar) to demonstrate motion and interaction
Human-Centric Approach: A history of using research and signals to balance technical capabilities with human wellbeing and user agency

Job Responsibility

Drive the Interaction Framework for Embodied AI: Establish and evolve the design patterns for real-time AI. You will define how AI surfaces across mobile, glasses, and future form factors, balancing proactive assistance with user control
Execute Multimodal Design Strategy: Lead the development of scalable interaction systems that integrate voice, vision, and gesture. You will design the feedback loops that make AI feel responsive, low-latency, and contextually aware
Define Behavioral UI: Beyond visual components, you will define the "personality" and pacing of AI interactions. You’ll ensure these agents feel human-centric, reliable, and helpful rather than intrusive
Strategic XFN Partnership: Partner with Product, ML Research, and Engineering to influence model behavior. You will use design as a lens to help the team prioritize data collection and model tuning based on UX needs (e.g., latency vs. accuracy)
Bridge Research and Product: Drive high-velocity prototyping for "zero-to-one" AI features. You will translate raw research (like live world-understanding) into production-ready product visions for the Family of Apps and Reality Labs
Design Leadership & Mentorship: Serve as a pillar of the MSL design community. You will unblock complex design challenges for the team, mentor L5/L6 designers, and raise the collective "quality bar" for AI design within the organization

What we offer

bonus
equity
benefits

New

Senior Researcher

We are seeking a highly capable Senior Researcher to push the boundaries of stre...

Location

United States

Salary:

210000.00 - 309000.00 USD / Year

AssemblyAI

Expiration Date

Until further notice

Requirements

Strong research background in speech recognition, with deep understanding of classic streaming architectures (RNN-T, CTC) and modern attention mechanisms
Expertise in LLMs and language modeling, with ability to bridge speech and language model research
Proficiency in PyTorch and JAX/Flax—you can move fluidly between frameworks and implement complex architectures from scratch
Experience with large-scale distributed training and the practical challenges of scaling speech models
Track record of publications at top venues (ICASSP, Interspeech, NeurIPS, ICML) or equivalent industry impact
Strong experimental methodology—systematic approach to ablations, careful baseline comparisons, and rigorous evaluation
Ability to translate research insights into production-ready solutions
comfort working at the interface of research and engineering
Excellent communication skills—can articulate complex technical ideas clearly and collaborate effectively across teams

Job Responsibility

Design and develop novel streaming ASR architectures, pushing the boundaries of accuracy-latency tradeoffs in production systems
Research and prototype LLM-assisted speech-to-text —exploring how large language models can enhance streaming speech recognition and understanding
Develop new algorithms for streaming speaker diarization, contextual biasing, and multilingual speech recognition
Drive research from initial experimentation through rigorous evaluation to production deployment, working closely with engineering teams
Conduct systematic experiments on internal and public benchmarks, with careful attention to evaluation methodology and statistical rigor
Contribute to technical publications and represent AssemblyAI's research at top venues
Collaborate on research direction and technical strategy, helping shape the roadmap for Speech AI capabilities

What we offer

competitive equity grants
100% employer-paid benefits
flexibility of being fully remote
401k match up to 4% for US-based full time team members

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

Contextual AI Research Engineer

Meta

Location:
United States , Sunnyvale

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Nice to have:

Additional Information:

Job Posted:
February 18, 2026

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