The Opportunity

Our AI teams build highly available, low-latency microservices using modern, cloud-native technologies. This role sits within our broader AI organization and focuses on developing the platforms, services, and tooling that support AI-powered products — from inference and embeddings to APIs, data flows, and observability.

You’ll work in a fast-paced environment where reliability, performance, and usability matter just as much as innovation. While some squads work closer to inference pipelines and LLM tooling, others focus on platform foundations, troubleshooting and reliability, data systems, or observability — all critical to delivering AI in production at scale.

What You’ll Do

• Build, test, and deploy scalable microservices for AI-powered systems, including text and voice processing
  
  
• Design developer-friendly APIs, agents and internal tools that make AI easy to use across the Telnyx product ecosystem
  
  
• Contribute to AI inference, embeddings, and platform services that support real-time and low-latency workloads
  
  
• Optimize performance, reliability, and observability in production environments
  
  
• Collaborate closely with Product, Infrastructure, and ML teams to bring features from ideation to production
  
  
• Troubleshoot, debug, and support critical systems running in production
  
  
• Participate in code reviews and uphold high engineering and operational standards
  
  

Depending on the squad, your focus may lean more toward inference pipelines, platform foundations, observability, data systems, or production troubleshooting.

Who We’re Looking For

• Someone who has built something with cutting-edge AI tooling (something that has only become possible in the last 6 months, rolling from application date). It doesn't really matter what it is; we just want to know you are building and staying up to date.
  
  
• Strong understanding of async programming, concurrency, and parallel execution
  
  
• Experience with microservice-based systems
  
  
• Excellent communication skills and the ability to work effectively across teams
  
  

Nice to Haves

• Familiarity with LLM frameworks and tools (e.g. PyTorch, Transformers, DeepSpeed, vLLM)
  
  
• Experience with distributed computing frameworks such as Ray (Ray Core, Serve, Train)
  
  
• Exposure to cloud-native stacks (Docker, Kubernetes, Prometheus, Jaeger)
  
  
• Knowledge of LLM optimization techniques (e.g. quantization, speculative decoding)
  
  
• Background in Retrieval Augmented Generation (RAG) systems

How We Hire Across Our AI Teams

Our AI Chapter is made up of multiple squads, including:

• AI application & software engineering
  
  
• Platform & infrastructure foundations
  
  
• Troubleshooting, reliability, and production support
  
  
• Data, storage, and embeddings
  
  
• Observability and performance monitoring
  
  

We hire into a shared AI engineering pipeline. During interviews, we focus on core engineering skills, system design, and problem-solving ability. Final squad alignment happens later, based on:

• Your strengths and interests
  
  
• Team needs at the time
  
  
• Where you’ll have the biggest long-term impact
  
  

This means the exact focus of the role may vary by squad, but the core expectation remains the same: building reliable, scalable AI systems in production.

Why You’ll Love It Here

At Telnyx, we’re not just building products — we’re building the future of intelligent communication. Our TelnyxAI platform empowers developers and businesses to:

• Store and serve vector embeddings at scale
  
  
• Use open-source models with our hosted inference infrastructure
  
  
• Deploy multimodal AI features across text, voice, and storage seamlessly
  
  

You’ll have the autonomy to take ownership of meaningful projects, contribute ideas that shape the product roadmap, and collaborate with talented people who care deeply about impact, quality, and long-term thinking.

#LI-KG1
#LI-BRAZIL
#LI-INDIA

The Opportunity

Our AI teams build highly available, low-latency microservices using modern, cloud-native technologies. This role sits within our broader AI organization and focuses on developing the platforms, services, and tooling that support AI-powered products — from inference and embeddings to APIs, data flows, and observability.

You’ll work in a fast-paced environment where reliability, performance, and usability matter just as much as innovation. While some squads work closer to inference pipelines and LLM tooling, others focus on platform foundations, troubleshooting and reliability, data systems, or observability — all critical to delivering AI in production at scale.

What You’ll Do

• Build, test, and deploy scalable microservices for AI-powered systems, including text and voice processing
  
  
• Design developer-friendly APIs, agents and internal tools that make AI easy to use across the Telnyx product ecosystem
  
  
• Contribute to AI inference, embeddings, and platform services that support real-time and low-latency workloads
  
  
• Optimize performance, reliability, and observability in production environments
  
  
• Collaborate closely with Product, Infrastructure, and ML teams to bring features from ideation to production
  
  
• Troubleshoot, debug, and support critical systems running in production
  
  
• Participate in code reviews and uphold high engineering and operational standards
  
  

Depending on the squad, your focus may lean more toward inference pipelines, platform foundations, observability, data systems, or production troubleshooting.

Who We’re Looking For

• Someone who has built something with cutting-edge AI tooling (something that has only become possible in the last 6 months, rolling from application date). It doesn't really matter what it is; we just want to know you are building and staying up to date.
  
  
• Strong understanding of async programming, concurrency, and parallel execution
  
  
• Experience with microservice-based systems
  
  
• Excellent communication skills and the ability to work effectively across teams
  
  

Nice to Haves

• Familiarity with LLM frameworks and tools (e.g. PyTorch, Transformers, DeepSpeed, vLLM)
  
  
• Experience with distributed computing frameworks such as Ray (Ray Core, Serve, Train)
  
  
• Exposure to cloud-native stacks (Docker, Kubernetes, Prometheus, Jaeger)
  
  
• Knowledge of LLM optimization techniques (e.g. quantization, speculative decoding)
  
  
• Background in Retrieval Augmented Generation (RAG) systems

How We Hire Across Our AI Teams

Our AI Chapter is made up of multiple squads, including:

• AI application & software engineering
  
  
• Platform & infrastructure foundations
  
  
• Troubleshooting, reliability, and production support
  
  
• Data, storage, and embeddings
  
  
• Observability and performance monitoring
  
  

We hire into a shared AI engineering pipeline. During interviews, we focus on core engineering skills, system design, and problem-solving ability. Final squad alignment happens later, based on:

• Your strengths and interests
  
  
• Team needs at the time
  
  
• Where you’ll have the biggest long-term impact
  
  

This means the exact focus of the role may vary by squad, but the core expectation remains the same: building reliable, scalable AI systems in production.

Why You’ll Love It Here

At Telnyx, we’re not just building products — we’re building the future of intelligent communication. Our TelnyxAI platform empowers developers and businesses to:

• Store and serve vector embeddings at scale
  
  
• Use open-source models with our hosted inference infrastructure
  
  
• Deploy multimodal AI features across text, voice, and storage seamlessly
  
  

You’ll have the autonomy to take ownership of meaningful projects, contribute ideas that shape the product roadmap, and collaborate with talented people who care deeply about impact, quality, and long-term thinking.

#LI-KG1
#LI-BRAZIL

About us

Nu was born in 2013 with the mission to fight complexity to empower people in their daily lives by reinventing financial services. We are one of the world’s largest digital banking platforms, serving millions of customers across Brazil, Mexico, and Colombia. For more information, visit our institutional page https://international.nubank.com.br/careers/

Data Science at Nubank

Data Science is essential to every part of the business at Nubank, since Day 1. Most areas of the company use data science to some extent. Data Scientists are responsible for translating business needs into models and other types of data-driven solutions.

As a Data Scientist, you’re expected to

• Interact with other team members to understand how to best apply data science and artificial intelligence to Nubank’s problems;
• Investigate problems and discover insights through exploratory data analysis and other quantitative methods;
• Have great numerical and analytical literacy, including knowledge of statistics and linear algebra as needed;
• Work on multiple stages of the ML model lifecycle–from ideation to training and steady-state operation;
• Work across multiple types of models, algorithms and learning paradigms;
• Communicate technical points, decisions and tradeoffs to peers and stakeholders;
  
  

Our ideal candidate

• Has experience working with ML models in a production environment;
• Understands possible pitfalls and tradeoffs when applying ML to real-word, sometimes messy problems;
• Is familiar with the technical aspects of learning theory and algorithms and is able to discuss details if needed;
• Has experience working with the Python scientific stack (Numpy, Pandas, Scipy, Sklearn, Boosted Tree Libraries, etc);
• Has experience working with Tensor/Deep Learning libraries such as Tensorflow and Pytorch;
• Is able to connect analytical outcomes to business priorities and advise stakeholders on the best course of action;
• Has good communication skills and is able to convey technical topics and decision points to diverse audiences;
• Has experience writing general-purpose code using modern tools;
• Understands the implications of causality when applying ML to problems;
• Is up-to-date with recent developments in the area as a whole and is able to identify opportunities for improvement and innovation;
  
  

Our Benefits

• Chance of earning equity at Nubank
• Food/ Meal Card (Vale-Refeição and/or Vale Alimentação)
• Public Transportation Commuting Benefit (Vale-Transporte)
• NuCare – Psychological, Financial and Legal Assistance Program
• Life Insurance
• Medical Plan
• Dental Plan
• NuLanguage – Language Course Program
• Nucleo - Our learning platform of courses
• Extended Parental Leave
• Daycare Allowance
• Parental Consultancy
• Work-from-home Allowance
• Gym Partnerships
• 30 days of paid vacation
  
  

Work Model for this Role

Hybrid 2-3 times/week: Our hybrid work model brings us to the office at least twice a week, on strategic days designed to maximize team connection and collaboration. For more details, visit https://building.nubank.com/nu-hybrid-work-model/

A Capco é uma consultoria global de tecnologia e negócios, focada no setor de serviços financeiros e energia, somos apaixonados por ajudar nossos clientes, temos 40 escritórios nas Américas, Europa e Ásia-Pacífico! Se criatividade e inovação são sua paixão, a Capco é ideal para você. Vamos te apoiar e ajudar a acelerar sua carreira!

Estamos em busca de um(a) Machine Learning Engineer com foco em NLP e processamento de documentos para atuar no desenvolvimento de soluções inteligentes voltadas à automação e análise de dados, especialmente em contextos financeiros. O(a) profissional será responsável por construir pipelines de dados, desenvolver modelos de machine learning e implementar soluções escaláveis em ambiente cloud.

O que você fará:

• Desenvolver soluções de machine learning e NLP para extração e processamento de informações de documentos
• Trabalhar com OCR, parsing de PDFs e extração de dados de Excel
• Implementar algoritmos de fuzzy matching (ex: Levenshtein, record linkage)
• Construir e manter pipelines de dados e processos de ETL
• Desenvolver, treinar e validar modelos de machine learning (supervisionados e não supervisionados)
• Realizar deploy de modelos utilizando APIs REST, Docker e serviços Azure
• Integrar soluções com sistemas externos e aplicações corporativas
• Colaborar com times multidisciplinares para entrega de soluções escaláveis

O que você precisa ter:

• Forte experiência em Python (Pandas, NumPy, scikit-learn)
• Experiência com bibliotecas de NLP (spaCy, NLTK ou Transformers)
• Conhecimento em processamento de documentos (OCR, PDFs, Excel)
• Experiência com deploy de modelos (APIs REST, Docker, Azure ML)
• Entendimento de técnicas de machine learning supervisionado e não supervisionado
• Experiência com pipelines de dados e ETL
• 2 a 5 anos de experiência em Machine Learning, com foco em NLP ou dados financeiros
• Inglês avançado/fluente

Diferenciais

• Experiência no setor financeiro/fintech (reconciliação, contabilidade)
• Conhecimento em Azure Machine Learning e Cognitive Services
• Experiência com frameworks de deep learning (TensorFlow, PyTorch)
• Experiência com LLMs para entendimento de documentos (OpenAI, Azure OpenAI)

POR QUE CAPCO:

Na Capco promovemos uma cultura inclusiva. Valorizamos a diversidade em todas as suas expressões. 
Pensamos, em conjunto, sempre em ações diversas de inclusão e de responsabilidade social através de comitês internos geridos pela nossa comunidade interna, como os grupo de Mulheres, Pessoas Com Deficiência, Pessoas Negras, LGBTQIAPN+, Parentalidade, Gerações, entre outros. Nossas oportunidades são trabalhadas para todos(as)!
#LifeAtCapco

PRÓXIMOS PASSOS:

• Se você está ansioso(a) para progredir sua carreira conosco, candidate-se e aguarde o contato de um de nossos recrutadores!

Xometry (NASDAQ: XMTR) powers the industries of today and tomorrow by connecting the people with big ideas to the manufacturers who can bring them to life. Xometry’s digital marketplace gives manufacturers the critical resources they need to grow their business while also making it easy for buyers at Fortune 1000 companies to tap into global manufacturing capacity.

Xometry is looking for a Machine Learning Engineer II who is excited about advancing machine learning capabilities and bringing models into production at scale. In this role, you’ll design, deploy, and maintain robust statistical and machine learning models, working closely with data scientists to translate research and experimentation into reliable, high-impact systems. You’ll apply strong data intuition and engineering judgment to improve model performance, reliability, and observability, while building predictive models that support pricing, cost estimation, and sourcing recommendations.

What You'll Do:

• Design, build, and optimize machine learning models to enhance Xometry’s platform and business operations.
• Analyze large datasets to extract meaningful patterns and insights.
• Collaborate with cross-functional teams to integrate machine learning models into production systems.
• Learn and apply best practices in model evaluation, performance tuning, and deployment.
• Influence technical direction by identifying opportunities to improve modeling approaches, data quality, and system architecture.
• Work across teams to ensure machine learning solutions are explainable, maintainable, and aligned with business goals.
• Help bridge the gap between research and production, ensuring models perform just as well in the real world as they do in notebooks.
• Gain exposure to cutting-edge machine learning frameworks, tools, and techniques used in the manufacturing industry.

Qualifications:

• A bachelor’s degree is required, but an advanced degree (M.S. or PhD) in computer science, machine learning, AI, or a related field is highly preferred.
• Experience deploying and maintaining machine learning models in production environments.
• 4+ years of experience in machine learning, focusing on data engineering and/or data science.
• Proficient in Python, including key libraries such as PyTorch, TensorFlow, pandas, and numpy.
• Strong background in probability, statistics, and optimization techniques relevant to generative modeling.
• Familiarity with cloud computing resources and tools for model training and deployment (e.g., AWS SageMaker).
• Familiar with software engineering principles, including version control, reproducibility, and continuous integration.
• Experience in the manufacturing, supply chain, or similar industries is a plus.

#LI-Remote

Xometry is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status.

For US based roles: Xometry participates in E-Verify and after a job offer is accepted, will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.

Xometry is seeking a Senior Machine Learning Engineer to join our growing organization. The right person will help move our machine learning capabilities to the next level. You’ll be working in an organization where AI is the enabler and center of its core business strategy. You want to be part of a small, intensely skilled team, who feel total ownership of their work, and can’t imagine a day without learning & coding.  You will play a crucial role in the Xometry platform and everything you do will matter.

Responsibilities:

• At Xometry, you will play a crucial role in exploring new machine learning opportunities, researching and performing proof of concepts, and bringing new machine learning and AI solutions into Xometry’s platform
• Develop and implement machine learning models that improve Xometry’s ability to predict cost, price, and sourcing options for our customers and suppliers.
• You will be responsible for leading the evaluation of emerging technologies, identifying areas for improvement, and developing new features while ensuring the reliability and scalability of Xometry’s platform
• Lead the exploration of emerging AI and machine learning technologies and develop proof-of-concepts to assess their potential impact on Xometry’s platform
• Collaborate with cross-functional teams to gather requirements, prioritize features, and define technical solutions based on the latest innovations
• Monitor machine learning models and AI performance and troubleshoot issues as they arise
• Contribute to the documentation and knowledge base to help other teams understand and use Xometry’s AI effectively

Qualifications:

• Experience with state of the art ML modeling techniques and approaches like transformers, self supervised pre-training, generative modeling, LLMs, etc
• Experience with large scale data processing (e.g., Hands-on experience training and applying models at scale using deep learning frameworks like PyTorch or Tensorflow)
• Successful candidates in this role need to be able to bridge state of the art approaches to real world impact
• A cloud-native software craftsperson with hands on experience with containers, container orchestration, and distributed systems
• An engineer with a self-driven attitude who can own problems and deliver solutions
• Strong software fundamentals with experience in design patterns, refactoring, OOP, and testing
• A cloud practitioner who values the “shift-left” mentality by building systems with Infrastructure as Code, not console clicking
• Data’s at the heart of our systems, we hope it's yours too. You’re comfortable working with SQL and/or NoSQL, understand database design, and data analysis
• Experience building and consuming CI/CD pipelines
• Someone who knows their way around the command line and has experience working with *nix systems
• 5+ years working experience in the engineering teams that build large-scale ML-driven user-facing products
• 3+ years experience leading cross-team engineering efforts
• Strong execution skills in project management

#LI-Remote

Xometry is seeking a Senior Machine Learning Engineer to join our growing organization. The right person will help move our machine learning capabilities to the next level. You’ll be working in an organization where AI is the enabler and center of its core business strategy. You want to be part of a small, intensely skilled team, who feel total ownership of their work, and can’t imagine a day without learning & coding.  You will play a crucial role in the Xometry platform and everything you do will matter.

Responsibilities:

• At Xometry, you will play a crucial role in exploring new machine learning opportunities, researching and performing proof of concepts, and bringing new machine learning and AI solutions into Xometry’s platform
• Develop and implement machine learning models that improve Xometry’s ability to predict cost, price, and sourcing options for our customers and suppliers.
• You will be responsible for leading the evaluation of emerging technologies, identifying areas for improvement, and developing new features while ensuring the reliability and scalability of Xometry’s platform
• Lead the exploration of emerging AI and machine learning technologies and develop proof-of-concepts to assess their potential impact on Xometry’s platform
• Collaborate with cross-functional teams to gather requirements, prioritize features, and define technical solutions based on the latest innovations
• Monitor machine learning models and AI performance and troubleshoot issues as they arise
• Contribute to the documentation and knowledge base to help other teams understand and use Xometry’s AI effectively

Qualifications:

• Experience with state of the art ML modeling techniques and approaches like transformers, self supervised pre-training, generative modeling, LLMs, etc
• Experience with large scale data processing (e.g., Hands-on experience training and applying models at scale using deep learning frameworks like PyTorch or Tensorflow)
• Successful candidates in this role need to be able to bridge state of the art approaches to real world impact
• A cloud-native software craftsperson with hands on experience with containers, container orchestration, and distributed systems
• An engineer with a self-driven attitude who can own problems and deliver solutions
• Strong software fundamentals with experience in design patterns, refactoring, OOP, and testing
• A cloud practitioner who values the “shift-left” mentality by building systems with Infrastructure as Code, not console clicking
• Data’s at the heart of our systems, we hope it's yours too. You’re comfortable working with SQL and/or NoSQL, understand database design, and data analysis
• Experience building and consuming CI/CD pipelines
• Someone who knows their way around the command line and has experience working with *nix systems
• 5+ years working experience in the engineering teams that build large-scale ML-driven user-facing products
• 3+ years experience leading cross-team engineering efforts
• Strong execution skills in project management

#LI-Remote

About Us

Nu was born in 2013 with the mission to fight complexity to empower people in their daily lives by reinventing financial services. We are one of the world’s largest digital banking platforms, serving millions of customers across Brazil, Mexico, and Colombia.

About the role

At AI Core, we are scaling the impact of our AI initiatives to become the primary driver of Nubank’s most critical decision systems. We are seeking an Lead Machine Learning Engineer (Applied AI Scientist) to lead high-impact research projects that bridge the gap between state-of-the-art AI and production-grade financial systems. You will be responsible for solving complex, ambiguous problems using Deep Learning and Foundation Models, ensuring our architectures are scalable, efficient, and driving measurable business results.

As an Applied AI Scientist (MLE), you’re expected to:

1. Research Execution & Technical Leadership (Complexity & Autonomy)

• Lead and execute complex applied research initiatives independently, focusing on building and optimizing architectures (e.g., Transformers, GNNs) that can be deployed across critical use cases like Credit, RecSys, GenAI, and real-time inference.
• Address difficult and ambiguous modeling problems that require coordination across various stakeholders (Data, Infra, Product), delivering innovative solutions with a clear focus on medium-term impact.
• Bridge the gap between research and production by designing architectures that respect MLOps constraints, ensuring models are optimized for latency, interpretability, and cost-efficiency.

1. Strategic Impact & Collaboration (Impact)

• Develop and deliver innovative solutions that address project-level challenges, focusing on pushing the latest platform and AI research improvements into downstream production models.
• Actively participate in cross-functional collaborations, ensuring that research outputs are seamlessly integrated into Nubank's decision-making engines.
• Establish technical standards within the AI Core team for experimentation, model evaluation, and code quality, inspiring peers to raise their performance.

1. Mentorship & Function Contribution (Function Contribution)

• Serve as a technical mentor for senior engineers and researchers, providing guidance on deep learning fundamentals, problem formulation, and research methodology.
• Actively contribute to the function's growth by participating in mandatory activities like hiring (interview panels) and leading internal task forces to improve our ML lifecycle.
• Contribute to thought leadership by participating in research collaborations or internal papers that align with Nubank’s strategic goals.

What are we looking for?

• Professional Experience: 5-7+ years in applied AI/ML, with a proven track record of delivering research-driven systems into production environments
• Technical Mastery:
  • Deep expertise in Deep Learning architectures (Transformers, Multimodal, or GNNs).
  • Strong coding skills in Python and proficiency with frameworks like PyTorch, JAX, or TensorFlow.
  • Solid understanding of MLOps and the constraints of deploying models at scale.
• Problem Solving: Sophisticated skills in ML problem formulation and the ability to navigate uncertainty when data is messy or unavailable.
• Communication: Ability to communicate complex technical concepts to both technical peers and cross-functional stakeholders, ensuring alignment and buy-in.
• Analytical Capacity: Experience with large-scale experimentation and A/B testing to validate research hypotheses.

Our Benefits

• Chance of earning equity at Nubank
• Food/ Meal Card (Vale-Refeição and/or Vale Alimentação)
• Public Transportation Commuting Benefit (Vale-Transporte)
• NuCare – Psychological, Financial and Legal Assistance Program
• Life Insurance
• Medical Plan
• Dental Plan
• NuLanguage – Language Course Program
• Nucleo - Our learning platform of courses
• Extended Parental Leave
• Daycare Allowance
• Parental Consultancy
• Work-from-home Allowance
• Gym Partnerships
• 30 days of paid vacation
• Relocation Assistance Package, if applicable

Work Model for this Role

Hybrid 2-3 times/week: Our hybrid work model brings us to the office at least twice a week, on strategic days designed to maximize team connection and collaboration. For more details, visit https://building.nubank.com/nu-hybrid-work-model/

Principais Atividades:

• Desenvolver e manter APIs e microservices com tecnologias modernas.
• Trabalhar com arquitetura de software, garantindo escalabilidade e segurança.
• Atuar com dados e analytics, utilizando ferramentas como SQL, Power BI, Python, Spark e plataformas de Big Data.
• Criar e otimizar soluções em Cloud Computing (AWS, Azure, GCP), com práticas DevOps e CI/CD.
• Participar de times ágeis (Scrum, Kanban) e colaborar em projetos inovadores para grandes empresas

Requisitos:

• 5-6 anos de experiência sólida experiência comprovada em desenvolvimento de software com foco em inteligência artificial;
• Graduação em Ciência da Computação, Engenharia, Matemática ou área relacionada
• Proficiência em Python e experiência com bibliotecas como TensorFlow, PyTorch, Scikit-learn, etc;
• Conhecimento em LLM (Linguagem de Modelagem Lógico) e RAG (Rede Adaptativa Generativa) é altamente desejável;
• Experiência em trabalhar com serviços em nuvem, especialmente AWS;
• Excelentes habilidades de resolução de problemas e capacidade de trabalhar de forma independente e em equipe;
  Inglês intermediário/avançado (possivel atuação com time internacional).

Por que a Capco:

Na Capco, promovemos uma cultura inclusiva. Valorizamos a diversidade em todas as suas expressões. Pensamos, em conjunto, sempre em ações diversas de inclusão e de responsabilidade social através de comitês internos geridos pela nossa comunidade, como os grupo de Mulheres, Pessoas Com Deficiência, Pessoas Negras, LGBTQIAPN+, Parentalidade, Gerações, entre outros. Juntar-se à Capco significa ingressar em uma organização comprometida com um ambiente de trabalho inclusivo onde você é incentivado a #BeYourselfAtWork (Ser Você Mesmo no Trabalho). Celebramos a individualidade e reconhecemos que a diversidade e a inclusão, em todas as formas, são fundamentais para o sucesso. Acreditamos que todos trazem algo diferente, por isso adoraríamos saber o que o torna diferente! #LifeAtCapco
Juntar-se à Capco significa ingressar em uma organização comprometida com um ambiente de trabalho inclusivo onde você é incentivado a #BeYourselfAtWork (Ser Você Mesmo no Trabalho). Celebramos a individualidade e reconhecemos que a diversidade e a inclusão, em todas as formas, são fundamentais para o sucesso. Acreditamos que todos trazem algo diferente, por isso adoraríamos saber o que o torna diferente!

Próximos Passos:

O objetivo da Capco é conduzir um processo flexível e alinhado às necessidades de cada oportunidade e talento.

• Etapa 1: Entrevista comportamental.
• Etapa 2: Entrevista técnica.
• Etapa 3: Conversa com time de Projeto/ Delivery.
• Etapa 4: Conversa com cliente.
• Etapa 5: Proposta ou feedback.

As etapas do nosso processo seletivo descritas são essenciais para garantir uma avaliação completa e assertiva. Contudo, elas podem ser ajustadas dependendo da senioridade do(a) candidato(a), da área de atuação e do formato do projeto.