Research Engineer - Contextual AI Job at Meta (Redmond)

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

New

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

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

New

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

Data Scientist

This role is ideal for an AI professional who thrives in designing LLM-driven pi...

Location

Salary:

Not provided

HurixDigital

Expiration Date

Until further notice

Requirements

2–4 years of experience in Data Science, AI/ML, and Deep Learning, preferably in enterprise settings
Strong experience with Python, TensorFlow/Keras, Scikit-learn, and NLP frameworks such as SpaCy, HuggingFace, and NLTK
Proven expertise in Generative AI systems, including RAG architecture, vector-based search, and prompt engineering
Solid hands-on experience with Azure Cloud Platform, including services like Azure OpenAI, Cosmos DB, Key Vault, Blob Storage, Function Apps, etc.
Proficiency with FastAPI, Flask, and RESTful API design
Experience deploying models and services using Docker, Kubernetes, and Azure DevOps
Familiarity with Power Platform (Power BI, Power Apps, Power Automate) and SharePoint integration

Job Responsibility

Architect and implement Retrieval-Augmented Generation (RAG) pipelines using tools like LangChain, LlamaIndex, and Azure AI Search
Design and coordinate agent-based LLM systems using frameworks like AutoGen, TaskWeaver, and CrewAI for complex document analysis and process automation
Integrate Azure Cognitive Services (OCR, layout analysis, document intelligence) for structured data extraction and real-time insight generation
Develop secure and scalable FastAPI backends, containerized via Docker and orchestrated on Azure Kubernetes Service (AKS)
Collaborate with business experts to fine-tune prompts, build chatbots with contextual memory, and deploy solutions that meet compliance and audit standards
Build low-code applications using Power Apps and Power Automate to streamline enterprise workflows like workforce planning and financial tracking
Monitor model performance using Azure Application Insights, iterate on user feedback, and maintain operational excellence with CI/CD pipelines
Contribute to AI research and publications and stay updated with the latest trends in ethical AI and edge deployment strategies

Fulltime

Product Engineer Intern

We’re looking for an Product Engineer Intern to join our newly formed R&D squad....

Location

France , Paris

Salary:

1300.00 - 1500.00 EUR / Month

Beamy

Expiration Date

Until further notice

Requirements

You're french speaking (native)
You are in Bac +4 or Bac +5 of engineering school (Ecole Polytechnique, Télécom Paris, Centrale Supélec…)
You thrive in uncertain, exploratory environments and enjoy solving open-ended problems. Brain-teasers don’t frighten you
You’re a fast learner who enjoys picking up new tools, languages, and methodologies.
You love rapid prototyping and can balance speed with technical rigor.
You enjoy working with data, AI, software eng. and tech in its globality to create impactful features in our product
You want to join an innovative and fast growing company that aims at climbing mountains

Job Responsibility

Prototype and validate new ideas: Develop quick, functional proofs of concept to test innovative product features.
Use cutting edge techs: Apply AI, NLP, and automation to enrich our 50K+ SaaS catalog and improve detection accuracy or behaviours triggers in our extension
Explore new interaction paradigms: Develop new ways for our users to interact with our web browser extension, via AI, contextual notifications etc
Extract insights from massive datasets: Work with our data stack (BigQuery, dbt, python) to identify patterns and trends in SaaS usage across large enterprises.
Balance speed & quality: Deliver POCs quickly while ensuring a smooth handoff to the core engineering team for productionization.
End-to-end prototyping: From ideation and research to developing MVPs and testing feasibility.
Exploration roadmap: Work closely with product and leadership to identify promising innovation areas.
Technical decision-making: Choose the right tools and architectures to validate hypotheses efficiently.
Cross-team collaboration: Share insights with engineering, data, and product teams to inform long-term strategy.

What we offer

Mentorship: Direct guidance from experienced developers
Real Impact: Work on actual product features and contribute to the company's growth
Benefits: Swile

Fulltime

Senior Data Scientist Personal Banking and Wealth Analytics

The Senior Data Scientist is a seasoned professional role. Applies in-depth disc...

Location

United States , Irving

Salary:

96400.00 - 144600.00 USD / Year

Citi

Expiration Date

January 31, 2026

Requirements

5-8 years experience in a combination of business and data analysis, process improvement and project management
5+ years in data science, machine learning, and AI system development preferred
Experience using tools for statistical modeling of large data sets
Strong proficiency in Python, PySpark, and LangChain, with a portfolio of projects involving RAG pipelines and agentic AI
Experience working with GCP Vertex AI, especially Gemini models, and deploying models in production environments preferred
Familiarity with vector databases and their role in semantic search and memory for AI agents preferred
Solid foundation in data analytics, including statistical modeling, data wrangling, and visualization
Ability to translate complex technical concepts into business value and communicate effectively with both technical and non-technical stakeholders
Strong knowledge in data engineering and data base concepts, able to identify right data elements needed for the solution
Financial services industry work experience preferred

Job Responsibility

Designs and manages vector databases (e.g., FAISS, Pinecone, or similar) to support semantic search and contextual memory in AI agents
Collaborates with cross-functional teams to integrate AI agents into business processes, enhancing automation, decision-making, and user experience
Conducts advanced data analysis and visualization to extract actionable insights from structured and unstructured data sources
Stays current with emerging trends in generative AI, LLM orchestration, and agentic systems to continuously improve solution design
Develops complex data & analytical solutions using python, Pyspark, SQL to identify the compliance/regulation issues
Identifies the right data elements needed for the solution and able to distinguish the critical data element vs non-critical data element
Develops and implement AI-driven solutions using Python, PySpark, and LangChain, with a focus on retrieval-augmented generation (RAG) architectures and agentic workflows
Leverages GCP Vertex AI, including Gemini models, to build scalable machine learning and generative AI applications
Conducts strategic data analysis, identifies insights and implications and make strategic recommendations, develops data displays that clearly communicate complex analysis
Mines and analyzes data from various banking platforms to drive optimization and improve data quality

What we offer

medical, dental & vision coverage
401(k)
life, accident, and disability insurance
wellness programs
paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays
discretionary and formulaic incentive and retention awards

Fulltime

AI Search Engineer

We're looking for an AI Search Engineer who possesses a deep understanding of la...

Location

United States , Mountain View

Salary:

120000.00 - 200000.00 USD / Year

Helpcare AI

Expiration Date

Until further notice

Requirements

Master's or PhD degree in Computer Science, Machine Learning, Statistics, or a related field
Strong programming skills in one or more programming languages, such as Python, or C++, and extensive experience with machine learning libraries, such as TensorFlow, PyTorch, Llama Index, LangChain etc.
Proven experience in developing and deploying complex machine learning models in production environments, including experience with cloud-based platforms, edge devices, or embedded systems
Strong understanding of advanced machine learning algorithms, such as deep learning, reinforcement learning, RAGs, and ensemble methods, and experience with model optimization techniques, such as hyper-parameter tuning, model compression, and quantization
Solid understanding of data pre-processing, feature engineering, and data quality assurance techniques, and experience with large-scale, complex data sets
Excellent problem-solving skills and ability to analyze and interpret complex data sets to extract meaningful insights and drive decision-making

Job Responsibility

RAG System Research and Implementation: Lead the design and implementation of advanced retrieval systems like Deep Memory by Activeloop, delivering optimized RAG systems across the entire value chain - from embedding or model fine-tuning to retrieval optimization with custom algorithms, to enhance knowledge retrieval accuracy
Search Algorithm Optimization: Develop and refine search algorithms, including semantic search, hybrid search, and multi-modal search techniques, to improve retrieval performance and relevance ranking
Vector Database Integration : Implement and optimize vector storage and indexing solutions within Deep Lake, ensuring efficient similarity search capabilities for high-dimensional embeddings used in RAG systems
Query Understanding and Processing: Design and implement advanced query processing pipelines, including query expansion, intent recognition, and contextual interpretation to enhance search precision
Information Retrieval Model Development: Create and fine-tune machine learning models specifically for information retrieval tasks, such as document ranking, query-document relevance scoring, and zero-shot retrieval
Performance Evaluation and Metrics: Establish comprehensive evaluation frameworks for search and RAG systems, including relevance assessments, A/B testing, and user satisfaction metrics to continually improve system performance
Scalability and Efficiency: Optimize RAG and search systems for high throughput and low latency, ensuring they can handle large-scale datasets and real-time query processing demands
Data Ingestion and Indexing: Develop efficient data ingestion pipelines and indexing strategies to support rapid updates and real-time search capabilities across diverse data types and sources

Fulltime

Research Engineer - Contextual AI

Meta

Location:
United States , Redmond

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Nice to have:

Additional Information:

Job Posted:
January 23, 2026

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