Research Engineer - Contextual AI Job at Meta (Redmond)

New

Principal Software Engineers - Applied AI for Microsoft Threat Protection

The Microsoft Security Organization is building the next generation of security ...

Location

United States , Redmond

Salary:

139900.00 - 274800.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, Python, C#, Go, or Java OR equivalent experience
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role
These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter
Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience
6+ years of experience designing, building and operating scalable ML systems, including ML infrastructure and pipelines (Azure ML, Kubernetes), model versioning, observability, and secure deployment, with hands‑on experience in MLOps/AIOps/SecDevOps practices
6+ years of experience building secure, reliable software systems, with applied knowledge of authentication, data protection, access control, and secure coding practices
6+ years of experience designing, building, and operating distributed or cloud‑scale systems (Azure, AWS, or GCP), including production ownership, CI/CD integration, and operating highly available services
2+ years of experience designing and building applications with LLM orchestration frameworks (e.g., LangChain, AutoGen), including agent‑based workflows, RAG pipelines, prompt engineering, and model fine‑tuning/evaluation

Job Responsibility

Design and evolve AI‑driven security systems leveraging large language models, multimodal models, and frontier capabilities to address complex security challenges
Develop contextual knowledge systems, including security graphs, semantic representations, memory frameworks, and high‑quality reasoning over security data
Collaborate across disciplines with Security Engineers, domain experts, and Product Managers to define inclusive, AI‑native security experiences
Partner with AI Infrastructure and Platform teams, Research, and Model Engineering groups to translate security workflows into AI‑optimized architectures
Enable automation, augmentation, and responsible autonomy to drive measurable functional improvements across security solutions
Prototype, validate, and deploy solutions in live production environments while upholding Microsoft standards for security, reliability, privacy, and trust
Shape technical direction for AI Security by influencing architecture, tooling, engineering practices, and shared best practices
Lead cross‑team initiatives spanning security products, platforms, and business units through collaboration and shared ownership
Mentor and sponsor engineers at multiple levels, fostering inclusive technical dialogue, sound engineering judgment, and continuous growth
Contribute to a culture of learning, accountability, and impact across the broader engineering and security community

Fulltime

Contextual AI Research Engineer

Meta Reality Labs Research (RL Research) brings together a industry-leading R&D ...

Location

United States , Sunnyvale

Salary:

217000.00 USD / Year ▼

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

Applied AI Engineer II

Project Sophia is a new generation business application, built ground up from ma...

Location

United States , Redmond

Salary:

100600.00 - 199000.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, OR related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field OR equivalent experience
Ability to meet Microsoft, customer and/or government security screening requirements
Microsoft Cloud Background Check
2+ years of extensive experience with one or more modern web technologies such as .NET / Node / React / Angular, building RESTful APIs
2+ years of solid experience in an OO Language like C# or Java or Python
1+ years of professional experience working with generative artificial intelligence, large language models, or agent-based systems
BS/MS in Computer Science or equivalent or 5+ years of industry experience
Excellence in one or more general programming languages including but not limited to: Python, C#
JavaScript
TypeScript

Job Responsibility

Design, implement, and ship AI-first product capabilities end-to-end from rapid prototype to production, spanning LLM-powered services, retrieval/grounding pipelines, and intelligent UX experiences that delight users through Sophia’s AI canvas
Own implementation across the full stack integrating front-end experiences, back-end services, and AI orchestration layers that connect models, context, and tools to deliver cohesive, extensible, high-performance systems
Collaborate with design, research, and platform teams to adapt or fine-tune LLMs/SLMs and multimodal models for real-world customer scenarios, ensuring outcomes are contextual, transparent, and human-centered
Build agentic, tool-using, and multimodal workflows that reason across data and services
optimize for safety, latency, reliability, and cost efficiency
Contribute to engineering excellence secure-by-design, accessibility compliance, automated testing, and code craftsmanship across the product lifecycle
Instrument and evaluate AI features with telemetry, experimentation, and continuous feedback loops to refine reasoning quality and user experience
Drive live-site reliability and operational excellence, participating in On-Call rotations while maintaining a sustainable, high-ownership engineering culture

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

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

Product Designer - RealTime AI

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

Location

United States , Menlo Park

Salary:

250000.00 - 312000.00 USD / Year

Sr Engineer, Machine Learning Engineering

The Senior Engineer, Machine Learning plays a pivotal role in advancing AI capab...

Location

United States , Bellevue; Atlanta; Overland Park; Herndon

Salary:

127000.00 - 229100.00 USD / Year

T-Mobile

Expiration Date

Until further notice

Requirements

Bachelor's Degree Computer Science, Data Science, Statistics, Informatics, Information Systems, Machine Learning, or another quantitative field
1+ year of experience in designing, developing, and deploying large language models (LLMs) and generative AI systems in production environments
5+ years of experience building and maintaining end-to-end ML pipelines, including data ingestion, training, deployment, monitoring, and optimization
3+ years of experience applying MLOps practices and leveraging cloud platforms (AWS, GCP, or Azure) for scalable AI solutions
5+ years of experience collaborating with cross-functional teams (engineering, data science, and product) to deliver AI-powered applications
2+ years of experience in programming languages such as Python/R, Java/Scala, and/or Go, with hands-on experience in frameworks such as PyTorch, TensorFlow, LangChain, or Hugging Face
At least 18 years of age
Legally authorized to work in the United States

Job Responsibility

Build and manage the complete machine learning and generative AI lifecycle, including research, design, experimentation, development, deployment, monitoring, and maintenance
Design, develop, and deploy LLM-based and generative AI models to power scalable and intelligent enterprise applications
Architect, optimize, and maintain retrieval-augmented generation (RAG), prompt orchestration, and contextual reasoning pipelines to support diverse AI use cases
Implement scalable MLOps pipelines for model deployment, performance monitoring, and continuous improvement
Conduct fine-tuning, alignment, and evaluation of LLMs and multimodal models to ensure reliability, efficiency, and fairness
Collaborate with data science, engineering, and product teams to translate business needs into generative AI-driven solutions
Perform benchmarking, evaluation, and optimization of generative models to improve accuracy, latency, and cost efficiency
Research and apply emerging techniques in transformer architectures, multimodal learning, and generative modeling to drive innovation and enhance enterprise capabilities
Ensure secure, ethical, and responsible AI deployment, embedding fairness, transparency, and compliance throughout the model lifecycle
Mentor and guide team members on generative AI frameworks, best practices, and experimentation methodologies

What we offer

Annual stock grant
Employee stock purchase plan
401(k)
Access to free, year-round money coaches
Medical, dental and vision insurance
Flexible spending account
Employee stock grants
Employee stock purchase plan
Paid time off
Up to 12 paid holidays

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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