Drive human data annotation, AI-assisted quality, and model and data evaluation across Reality Labs, focusing on perception and generative AI experiences.
Locations (3)
Redmond, Washington, United States
Menlo Park, California, United States
Fremont, California, United States
Responsibilities
Own a portfolio of annotation and evaluation programs across Meta Reality Labs' perception and generative AI experiences.
Partner with research scientists, engineers, and technical program managers to translate model and evaluation requirements into task designs, rubrics, rater guidelines, and acceptance criteria.
Operate, maintain, and extend existing program tooling, including task configurations, data pipelines, queries, dashboards, and automated reports.
Senior Software Engineer to build and evolve external integration strategy leveraging MCP and A2A, designing full‑stack features and AI‑powered capabilities.
Responsibilities
Design and implement full‑stack features across frontend and backend systems
Write high‑quality code daily
Collaborate with product, design, and platform partners
Deliver cohesive user experiences
Provide reliable estimates and take work from design through production
Requirements
BA or BS in Computer Science or equivalent practical experience
AI Regulatory Engineer to bridge AI development, systems engineering, clinical workflow, quality systems, and regulatory requirements for AI-enabled medical devices.
Responsibilities
Evaluate regulatory impact of AI model changes
Translate technical decisions into regulatory rationale
Develop and review technical evidence for AI product registrations
Lead technical analysis for regulatory deficiencies
Maintain traceability of product requirements and design decisions
Requirements
Master's degree or above in Biomedical Engineering, Computer Science, Medical Imaging, AI/ML, Software Engineering, or a related technical field
Lead the evolution of Cloud Billing/Zero Touch Billing strategies, reducing manual intervention in the billing cycle by bridging business, finance, and development teams to manage the automation roadmap and solution implementation.
Responsibilities
Liderar a evolução para um modelo de Faturamento Cloud Zero Touch, minimizando atividades manuais nos processos recorrentes de faturamento.
Automatizar o fluxo de ponta a ponta, desde o recebimento e a ingestão de dados de consumo/faturamento do fabricante até a preparação, validação, conciliação e processamento nos sistemas internos de faturamento/ERP.
Identificar atividades manuais, pontos de falha, exceções e dependências operacionais, transformando-os em oportunidades concretas de automação.
Projetar soluções utilizando APIs, integrações, fluxos de trabalho, RPA, scripts e inteligência artificial, selecionando a alternativa mais adequada para cada cenário.
Trabalhar com as equipes responsáveis pelo CIS e pelas demais plataformas do ecossistema Cloud para encaminhar requisitos que exijam desenvolvimento ou mudanças estruturais.
Requirements
Formação universitária em Tecnologia da Informação, Computação, Engenharia ou áreas relacionadas
AI Regulatory Engineer bridging AI development, systems engineering, clinical workflow, quality systems, and regulatory requirements for AI-enabled medical devices
Responsibilities
Evaluate regulatory impact of AI model changes
Translate technical decisions into regulatory rationale
Develop and review technical evidence for AI product registrations
Coordinate responses to regulatory authorities
Maintain traceability of product requirements and design decisions
Requirements
Master's degree or above in Biomedical Engineering, Computer Science, Medical Imaging, AI/ML, Software Engineering, or a related technical field
Nice to have: Medical imaging or healthcare AI products
Nice to have: Regulatory submissions for AI-enabled medical devices
Design, build, and operate reliable cloud platform capabilities for Expedia Group’s products at global scale.
Locations (2)
Chicago, Illinois, United States
Austin, Texas, United States
Compensation
The total cash range for this position in Chicago is $136,000.00 to $190,500.00. Employees in this role have the potential to increase their pay up to $217,500.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role. The total cash range for this position in Austin is $146,000.00 to $204,500.00. Employees in this role have the potential to increase their pay up to $233,500.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.
Responsibilities
Design, build, and operate reliable cloud platform capabilities that enable engineering teams to deliver and run services effectively.
Apply technical aptitude across infrastructure, automation, observability, security, and platform reliability to improve engineering outcomes.
Configure, implement, and enhance service mesh capabilities, including ingress controller patterns and Istio-based solutions, to support secure service-to-service communication and workload connectivity.
Senior Mobile Engineer, Flutter (iOS & Android) - Layla AI
Design, build, and maintain Layla’s cross‑platform mobile experience in Flutter (Dart), delivering a single, high‑quality codebase that performs reliably across iOS and Android.
Locations (2)
Seattle, Washington, United States
Austin, Texas, United States
Compensation
The total cash range for this position in Seattle is $184,500.00 to $258,000.00. Employees in this role have the potential to increase their pay up to $295,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.
The total cash range for this position in Austin is $184,500.00 to $258,000.00. Employees in this role have the potential to increase their pay up to $295,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.
Responsibilities
Design, build, and maintain Layla’s cross‑platform mobile experience in Flutter (Dart)
Own end‑to‑end feature delivery for mobile
Collaborate closely with Product, Design, and backend engineering
Drive mobile quality and reliability through automated testing, CI/CD, performance monitoring
Safely integrate and operate AI/ML‑enabled capabilities within the app
Define how quality is measured for each program: break down what a correct answer means into verifiable checks.
Design, configure, and operate AI and automation across the annotation pipeline, including pre-annotation, LLM and VLM judges, and quality triage.
Requirements
Bachelor's degree in a directly related field, or equivalent practical experience
Drive observability, capacity planning, system and service performance analysis, and environment tuning, while debugging issues across production and pre-production environments.
Advance continuous delivery practices by automating application and infrastructure deployments, integrating infrastructure as code into CI/CD pipelines, and detecting and remediating deployment issues.
Requirements
Bachelor’s degree in Computer Science or a related technical field; or Equivalent related professional experience.
Nice to have: designing and operating cloud platforms at scale
Nice to have: AI-driven systems
Nice to have: Service Mesh within Kubernetes
Nice to have: Advanced proficiency in Kubernetes tooling
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