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Advanced Packaging Reliability Engineer

openai

Híbrido San Francisco
Uncategorized

Job Score

80 pts
Hybrid model (+80)

About the Team:

OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI.

Role Overview

We are seeking a Package Reliability Engineer to lead reliability engineering for advanced packages used in high-performance AI and computing systems. The primary focus of this role is to assess package level mechanical and thermal reliability risks and apply thermal and mechanical modeling to optimize package design, material selection, and assembly processes. The engineer will also develop reliability test plans with external partners, identify failure mechanisms, perform root-cause analysis, and recommend practical corrective actions.

In this role, you will assess package reliability risks from early architecture development through product qualification and high-volume manufacturing. You will work closely with package design, silicon design, system engineering, manufacturing, and ASIC partners to predict package behavior, develop qualification strategies, resolve reliability issues, and improve overall package robustness and lifetime.

In this role you will:

  • Lead reliability test plan and assessments for advanced HPC packages, including risk identification, potential failure-mechanism analysis, root-cause investigation, mitigation planning, and corrective-action development.

  • Drive reliability-focused package design optimization based on thermo-mechanical modeling to improve package reliability, power integrity, thermal performance, mechanical robustness, and platform scalability.

  • Develop, validate, and apply package reliability models and lifetime-prediction methodologies for assembly, qualification, and product operating conditions.

  • Evaluate and recommend package architectures, structural designs, materials, and assembly processes to maximize reliability performance and manufacturing robustness.

  • Predict electromigration lifetime of package interconnects under product-specific current, temperature, workload, duty-cycle, and PCB boundary conditions.

You might thrive in this role if you have:

  • Enjoy solving complex reliability challenges associated with cutting-edge HPC packages, including very large package form factors, high power, and high-speed chip integration.

  • Are excited to develop new reliability test methodologies, predictive models, and engineering solutions rather than relying solely on conventional industry practices.

  • Are motivated by pushing the limits of heterogeneous verfical integration (chip/package/system), high-current power delivery, advanced cooling, and large-scale package architectures.

  • Want to influence product architecture and design decisions through simulation-driven insights across chip, package, cooling, and system levels.

  • Enjoy learning broadly across semiconductor technologies, including chip architecture, power delivery, package integration, materials, cooling, and system-level interactions.

Minimum Qualifications

  • 8+ years of industry experience & knowledge of semiconductor package reliability principles and failure mechanisms, including electromigration, solder-joint fatigue, interfacial delamination, dielectric cracking, via failure, warpage, creep, stress relaxation, and material degradation.

  • In-depth knowledge of advanced packaging architectures, including 2.5D and 3.5D integration, interposers, embedded bridges, chiplets, large package substrates, HBM integration, redistribution layers, and package-level power delivery.

  • Demonstrated experience leading package failure investigations, performing root-cause analysis, and implementing effective design, material, process, or manufacturing corrective actions.

  • Strong experience with thermal and mechanical finite-element modeling of packages, including temperature distribution, warpage, stress, strain, fatigue, and interfacial reliability.

  • Strong understanding of package-material behavior, including coefficient of thermal expansion, elasticity, viscoelasticity, plasticity, creep, adhesion, fracture toughness, thermal conductivity, and temperature-dependent properties.

Preferred Qualifications

  • Experience developing electromigration or interconnect lifetime models for solder joints, vias, redistribution layers, interposers, or package power-delivery structures.

  • Knowledge of package qualification methods, acceleration models, thermal cycling, power cycling, current-stress testing, and reliability lifetime extrapolation.

  • Familiarity with package failure-analysis techniques such as acoustic microscopy, X-ray imaging, cross-sectioning, scanning electron microscopy, and material characterization.

  • Experience supporting package-integrated voltage regulation, high-current power delivery, or high-transient-current AI and HPC products.

  • MS or PhD in Mechanical Engineering, Electrical Engineering, Materials Science, Physics, or a related technical field.

  • Strong communication, cross-functional collaboration, and technical leadership skills.

To comply with U.S. export control laws and regulations, candidates for this role may need to meet certain legal status requirements as provided in those laws and regulations.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. 

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.

Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.

To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.

We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.

OpenAI Global Applicant Privacy Policy

At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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Jornalismo, RP, Comunicacao Corporativa, Marketing de Conteudo e Producao Multimidia.

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Gestao de Empresas, RH, Logistica, Consultoria, Gestao de Projetos e Empreendedorismo.

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Ciencia de Dados, Engenharia de Dados, BI, Machine Learning e IA. Da formacao ao mercado.

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Dica do Especialista

O Novo Jogo do Marketing Digital em 2026

O mercado de marketing digital em 2026 consolidou uma ruptura definitiva: o conteúdo que apenas informa tornou-se commodity. Se anos atrás a briga era por "produzir em volume para ser visto", o avanço exponencial da Inteligência Artificial Generativa e das regras de privacidade mudou o foco. O marketing digital hoje exige uma abordagem preditiva, altamente técnica e, paradoxalmente, muito mais humana.

Neste cenário maduro, não basta dominar ferramentas de anúncios ou publicar nas redes sociais. A disputa agora acontece nos bastidores tecnológicos: na gestão de dados primários, na integração do marketing com vendas e na capacidade de criar uma marca com autoridade inquestionável.

1. O Fim do "Hacking" e a Ascensão do First-Party Data (Dados Proprietários)

Com regulamentações rígidas de privacidade globais e o fim do suporte a cookies de terceiros pelos principais navegadores, as estratégias baseadas em "perseguir" o usuário pela web perderam força. O novo ativo mais valioso de uma empresa chama-se First-Party Data (dados coletados diretamente do consumidor, com consentimento).

Empresas que passaram os últimos anos construindo bases sólidas de leads e clientes (Inbound Marketing) possuem uma vantagem absurda sobre concorrentes que dependem exclusivamente do tráfego pago (Outbound) e de algoritmos do Google ou da Meta.

Ação Prática: O "Muro de Conteúdo"

Em 2026, marcas estão investindo pesadamente em plataformas próprias, comunidades e conteúdos premium que exigem cadastro (e-mail, preferências de consumo) para acesso, fugindo da dependência das redes sociais de terceiros.

2. IA Integrada, mas "Fadiga do Fake" no Conteúdo

A Inteligência Artificial já é rotina para a esmagadora maioria dos profissionais de marketing. Ferramentas como LLMs (modelos de linguagem grandes) otimizam processos, geram copies básicos, estruturam automações complexas (CRM) e prevêem comportamentos do usuário. No entanto, o uso da IA para Geração de Conteúdo em Massa fracassou.

"O mercado já batizou o movimento de ‘fadiga do fake’: a rejeição crescente a conteúdo genérico, perfeitamente estruturado, mas sem substância, ponto de vista ou experiência real."

Para se destacar em 2026, as marcas precisam comprovar o E-E-A-T (Experiência, Expertise, Autoridade e Confiabilidade). Os motores de busca e de IA (como Perplexity e ChatGPT Search) priorizam respostas que trazem vivência humana e opiniões de especialistas de nicho, penalizando textos robóticos ou puramente informativos.

3. SEO Multimodal e Social SEO

As buscas deixaram de ser exclusivas do Google e do formato de texto. Hoje, o SEO é fragmentado em duas grandes frentes que não podem mais ser ignoradas:

  • Busca Generativa e Multimodal (GEO): Otimização não apenas para links, mas para que a IA resuma a sua marca como "A" resposta para o usuário. Isso envolve dados estruturados perfeitos e otimização para buscas por voz e imagem (Google Lens).
  • Social SEO: O TikTok, Instagram e YouTube se tornaram os buscadores primários para as novas gerações. Em 2026, criar conteúdo otimizado com palavras-chave dentro das próprias redes sociais é tão vital quanto ranquear em motores tradicionais.

4. O Profissional de 2026: Obsessão por Performance e Growth

Para quem busca atuar na área, o mercado esfriou para o "especialista em apertar botões" (o gestor de mídias sociais genérico). As grandes oportunidades estão concentradas na intersecção entre criatividade, vendas e dados. As carreiras mais valorizadas são:

  • Growth Marketers e Especialistas em CRO (Otimização de Conversão): Profissionais focados em encontrar gargalos no funil de vendas, melhorando a experiência do usuário em landing pages e retendo clientes.
  • Analistas de Dados / Power BI no Marketing: Quem consegue comprovar o Retorno sobre Investimento (ROI) de cada real gasto, integrando os dashboards de marketing diretamente às metas do time comercial.
  • Estrategistas de Automação e CRM: O foco mudou do simples "disparo de e-mail" para a automação inteligente preditiva, que personaliza a comunicação no tempo certo, com a mensagem exata.

Conclusão

Em 2026, o marketing digital de sucesso é aquele que automatiza e escala a operação tecnológica através da inteligência artificial e uso inteligente de dados, mas mantém a estratégia, a empatia e a conexão humana como diferenciais insubstituíveis. O marketing não é mais sobre ser visto em todo lugar; é sobre ser relevante no lugar exato.