10.668 Empregos para Profissionais De Inteligência Artificial - Brasil

A Board Academy é um time apaixonado por inovação e transformação. Somos uma empresa especializada na Formação, Desenvolvimento e Certificação de Conselheiros, criada para revolucionar o modelo tradicional de desenvolvimento de conselheiros. Nossa proposta é disruptiva e, ao mesmo tempo, busca democratizar o acesso às posições nos Conselhos de Empresas.

Acreditamos que a formação profissional é essencial para a disseminação das boas práticas de governança corporativa e pode ser um grande diferencial na geração de valor e no sucesso dos negócios.

Missão do Cargo

Buscamos um Deep Learning Engineer para atuar no desenvolvimento de soluções baseadas em inteligência artificial com foco em redes neurais profundas. Essa pessoa será responsável por estruturar, treinar e otimizar modelos de deep learning aplicados às nossas soluções educacionais, operacionais e estratégicas.

Se você tem paixão por IA, gosta de construir soluções escaláveis e quer gerar impacto real com tecnologia de ponta, essa vaga é para você!

Responsabilidades e Atribuições

• Desenvolver, treinar e implementar modelos de deep learning aplicados a problemas reais de negócio;
• Trabalhar com dados estruturados e não estruturados (texto, imagem, voz);
• Colaborar com times de produto, dados e negócios para identificar oportunidades de aplicação de IA;
• Monitorar e melhorar a performance de modelos em produção;
• Documentar processos e garantir reprodutibilidade e boas práticas de engenharia de IA;
• Acompanhar avanços da área e propor inovações tecnológicas para o Board AI.

Requisitos

• Sólida experiência com desenvolvimento de modelos de deep learning (CNN, RNN, Transformers etc.);
• Domínio de bibliotecas como TensorFlow, PyTorch ou similares;
• Experiência prática com tratamento de dados, pré-processamento e pipelines de machine learning;
• Conhecimentos em MLOps, versionamento de modelos e deploy em ambientes de produção;
• Familiaridade com nuvens públicas (AWS, GCP ou Azure) e ferramentas de CI/CD;
• Diferencial: experiência com LLMs (Large Language Models) e NLP.

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A Board Academy é um time apaixonado por inovação e transformação.
Somos uma empresa especializada na Formação, Desenvolvimento e Certificação de Conselheiros, criada para revolucionar o modelo tradicional de desenvolvimento de conselheiros. Nossa proposta é disruptiva e, ao mesmo tempo, busca democratizar o acesso às posições nos Conselhos de Empresas.

Acreditamos que a formação profissional é essencial para a disseminação das boas práticas de governança corporativa e pode ser um grande diferencial na geração de valor e no sucesso dos negócios.

Missão do Cargo

Buscamos um Deep Learning Engineer para atuar no desenvolvimento de soluções baseadas em inteligência artificial com foco em redes neurais profundas. Essa pessoa será responsável por estruturar, treinar e otimizar modelos de deep learning aplicados às nossas soluções educacionais, operacionais e estratégicas.

Se você tem paixão por IA, gosta de construir soluções escaláveis e quer gerar impacto real com tecnologia de ponta, essa vaga é para você!

Responsabilidades e Atribuições

• Desenvolver, treinar e implementar modelos de deep learning aplicados a problemas reais de negócio;
• Trabalhar com dados estruturados e não estruturados (texto, imagem, voz);
• Colaborar com times de produto, dados e negócios para identificar oportunidades de aplicação de IA;
• Monitorar e melhorar a performance de modelos em produção;
• Documentar processos e garantir reprodutibilidade e boas práticas de engenharia de IA;
• Acompanhar avanços da área e propor inovações tecnológicas para o Board AI.

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Estamos em busca de um(a) Especialista em Deep Learning (Visão Computacional) para se juntar à nossa missão de combater fraudes de forma inovadora e eficiente. Para esta vaga, buscamos uma pessoa entusiasta por pesquisa e por aplicar o estado da arte em Inteligência Artificial para resolver problemas complexos. O foco principal do trabalho é a pesquisa constante de novas arquiteturas, modelos e estratégias que possam elevar o nível da nossa detecção de fraudes, principalmente as que envolvem análise de documentos e provas de vida (liveness detection).

Suas Responsabilidades:

Conduzir pesquisas aprofundadas sobre arquiteturas, modelos e técnicas de Deep Learning para a prevenção de fraudes.
Desenvolver e implementar soluções de Visão Computacional para análise de documentos e detecção de liveness.
Atuar ativamente na criação, curadoria e manutenção de datasets de alta qualidade para o treinamento de modelos.
Definir arquiteturas, treinar e otimizar modelos de deep learning, garantindo a melhor performance e acuracidade.
Avaliar de forma contínua o desempenho dos modelos em produção, identificando e corrigindo possíveis desvios ou oportunidades de melhoria.
Propor e executar novas abordagens e projetos, trazendo insights valiosos para a evolução constante dos nossos produtos de segurança.


Contratação PJ - Híbrido São Paulo - Brooklin

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Overview

Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for top architects, system and software engineers capable of using ML, Generative AI and other techniques to design, evangelize, implement and fine tune state-of-the-art solutions for never-before-solved problems.

Responsibilities

• Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions to address real-world challenges
• Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production
• Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholders
• Provide customer and market feedback to product and engineering teams to help define product direction

About The Team

Diverse Experiences. Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS. Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture. Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship and Career Growth. We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance. We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Basic Qualifications

• Bachelor of Science degree in Computer Science, or related technical, math, or scientific field (or equivalent experience)
• 3+ years of experience in designing, building, and/or operating cloud solutions in a production environment
• 2+ year experience hosting and deploying ML solutions (e.g., for training, fine tuning, and inference)
• 2+ years of hands on experience with Python to build, train, and evaluate models
• 2+ years of technical client engagement experience
• Ability to communicate in a business setting in English

Preferred Qualifications

• Masters or PhD degree in computer science, or related technical, math, or scientific field
• Strong working knowledge of deep learning, machine learning, generative AI, and statistics
• Experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker
• Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients
• Experience building cloud solutions with AWS

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Company - Amazon AWS Services Brazil Ltd

Job ID: A

Seniority level

• Not Applicable

Employment type

• Full-time

Job function

• Research, Science, and Engineering

Industries

• IT Services and IT Consulting

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Description
Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI.
The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently.
You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.
We're looking for top architects, system and software engineers capable of using ML, Generative AI and other techniques to design, evangelize, implement and fine tune state-of-the-art solutions for never-before-solved problems.
Key job responsibilities
- Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions to address real-world challenges
- Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production
- Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder
- Provide customer and market feedback to product and engineering teams to help define product direction
About the team
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.
Why AWS
Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship and Career Growth
We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.
Basic Qualifications
- Bachelor of Science degree in Computer Science, or related technical, math, or scientific field (or equivalent experience)
- 3+ years of experience in designing, building, and/or operating cloud solutions in a production environment
- 2+ year experience hosting and deploying ML solutions (e.g., for training, fine tuning, and inference)
- 2+ years of hands on experience with Python to build, train, and evaluate models
- 2+ years of technical client engagement experience
- Ability to communicate in a business setting in English
Preferred Qualifications
- Masters or PhD degree in computer science, or related technical, math, or scientific field
- Strong working knowledge of deep learning, machine learning, generative AI, and statistics
- Experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker
- Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients
- Experience building cloud solutions with AWS
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

Overview

Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI.

The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently.

You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.

We’re looking for top architects, system and software engineers capable of using ML, Generative AI and other techniques to design, evangelize, implement and fine tune state-of-the-art solutions for never-before-solved problems.

Key job responsibilities

• Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions to address real-world challenges
• Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production
• Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholders
• Provide customer and market feedback to product and engineering teams to help define product direction

A day in the life

Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

About the team

Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture

Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship and Career Growth

We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Basic Qualifications

- Bachelor of Science degree in Computer Science, or related technical, math, or scientific field (or equivalent experience)
- 5+ years of experience in designing, building, and/or operating cloud solutions in a production environment
- 4+ years experience hosting and deploying ML solutions (e.g., for training, fine tuning, and inference)
- 4+ years of hands on experience with Python to build, train, and evaluate models
- 4+ years of technical client engagement experience
- Ability to communicate in a business setting in English

Preferred Qualifications

- Masters or PhD degree in computer science, or related technical, math, or scientific field
- 3+ years experience working with deep learning, machine learning, generative AI, or statistics
- Experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker
- Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients
- Experience building cloud solutions with AWS

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Posted: April 18, 2025 (Updated about 10 hours ago)

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Posted: September 29, 2025 (Updated 1 day ago)

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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Description
Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI.
The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently.
You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.
We're looking for top architects, system and software engineers capable of using ML, Generative AI and other techniques to design, evangelize, implement and fine tune state-of-the-art solutions for never-before-solved problems.
Key job responsibilities
- Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions to address real-world challenges
- Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production
- Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder
- Provide customer and market feedback to product and engineering teams to help define product direction
A day in the life
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon's culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
About the team
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.
Why AWS
Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship and Career Growth
We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.
Basic Qualifications
- Bachelor of Science degree in Computer Science, or related technical, math, or scientific field (or equivalent experience)
- 5+ years of experience in designing, building, and/or operating cloud solutions in a production environment
- 4+ years experience hosting and deploying ML solutions (e.g., for training, fine tuning, and inference)
- 4+ years of hands on experience with Python to build, train, and evaluate models
- 4+ years of technical client engagement experience
- Ability to communicate in a business setting in English
Preferred Qualifications
- Masters or PhD degree in computer science, or related technical, math, or scientific field
- 3+ years experience working with deep learning, machine learning, generative AI, or statistics
- Experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker.
- Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients
- Experience building cloud solutions with AWS
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

Overview

Já pensou em levar sua experiência para um time que estimula a inovação todos os dias?

Na Doutor-IE, ser um Doctor é fazer parte de um time apaixonado por tecnologia e movido pelo propósito de transformar o mercado automotivo com soluções inteligentes. Aqui, trabalhamos com ética, transparência e foco no que realmente importa: entregar o melhor para nossos clientes e crescer juntos.

Estamos com uma oportunidade para Consultor(a) em Machine Learning / Deep Learning! Buscamos pessoas especialistas em dados, tecnologia e inovação, com sólida experiência em projetos de IA em produção.

Perfil que focamos

• Mínimo de 5 anos de atuação comprovada em projetos de IA, ML ou DL em produção
• Experiência consistente em concepção, desenvolvimento e implantação de soluções baseadas em dados
• Histórico de aplicação de práticas DevOps e MLOps em produção
• Experiência em arquitetura de soluções analíticas em larga escala
• Fundamentos em ML supervisionado, não supervisionado e por reforço; DL (CNN, RNN, Transformers); PLN (tokenização, embeddings, geração, avaliação); visão computacional (detecção, segmentação, pose, OCR)
• Experiência com frameworks: TensorFlow, PyTorch, Keras, Scikit-learn, Pandas, NumPy, Hugging Face
• Modelagem e treinamento de modelos: pré-processamento, engenharia de features, ajuste de hiperparâmetros, avaliação e tuning
• Experiência em MLOps: versionamento de modelos, rastreamento de experimentos, automação de pipelines, deploy e monitoramento contínuo
• Bancos de dados SQL, MongoDB e bancos vetoriais
• Engenharia de dados: ETL/ELT e pipelines escaláveis
• Plataformas em nuvem (AWS principalmente, GCP ou Azure)
• Análise exploratória e visualização de dados (Jupyter, Pandas, matplotlib, BI)
• Governança e qualidade de dados: catálogo, políticas de segurança, métricas de qualidade
• Automação CI/CD (GitLab CI, GitHub Actions)
• Contêineres e orquestração (Docker, Kubernetes)
• Monitoramento & logging (Grafana, Prometheus, ELK, Splunk)
• Controle de versão (Git git-flow, trunk-based, code review)
• Proficiência em Python e SQL (nível especialista)
• Desejável: conhecimentos em MongoDB, PHP e Flutter

Atitudes que esperamos de você

• Desenvolver e implantar soluções de IA/ML/DL em produção
• Projetar, documentar e otimizar APIs RESTful (FastAPI, Flask) para servir modelos
• Estruturar pipelines de dados escaláveis
• Realizar análise exploratória de dados e gerar visualizações
• Colaborar com o time, garantindo qualidade, segurança e governança
• Atuar com mentalidade de melhoria contínua e inovação

Diferenciais

• Certificações em IA/ML (ex: AWS MLS-C01, GCP ML Engineer, Azure AI Engineer)
• Contribuições em comunidades open-source de IA/ML (ex: GitHub, Hugging Face)
• Experiência com LangChain/LangGraph, incluindo sistemas de RAG escaláveis

Cidade: Florianópolis - Santa Catarina

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Estamos em busca de uma pessoa Engenheira de Machine Learning para integrar nossa equipe de Soluções IA e ser responsável por aplicar técnicas de aprendizado de máquina em projetos inovadores, ajudando a construir soluções inteligentes para nossos produtos e clientes.

Se você possui paixão por tecnologia, tem conhecimentos em dados e está em busca de oportunidades para crescer na área, esta é a vaga ideal.

Responsabilidades:

• Projetar, desenvolver e implementar modelos de machine learning para resolver problemas de negócio diversos.
• Automatizar e otimizar processos relacionados ao ciclo de vida de modelos: desde a experimentação, treinamento, deploy até o monitoramento em produção.
• Trabalhar em colaboração com equipes de Ciência de Dados, Engenharia de Dados e Produto, garantindo que os modelos sejam integrados de forma eficiente aos sistemas.
• Garantir a escalabilidade, eficiência e confiabilidade das soluções de machine learning em ambientes de produção.
• Participar da definição de arquiteturas e pipelines de MLOps para automação e governança de modelos.
• Monitorar o desempenho dos modelos e ajustar parâmetros conforme mudanças nos dados e nos objetivos de negócio.
• Documentar soluções, boas práticas e contribuir para a evolução contínua dos processos e padrões técnicos.
• Pesquisar e implementar novas técnicas e ferramentas que impulsionem a inovação em machine learning.

Requisitos:

• Graduação completa ou em andamento em Ciência da Computação, Engenharia, estatística, matemática, ou áreas correlatas.
• Programação em Python ou outras linguagens adequadas para machine learning.
• com bibliotecas e frameworks de machine learning e deep learning (ex.: Scikit-learn, TensorFlow, PyTorch).
• Conhecimento de fundamentos de estatística, aprendizado supervisionado e não supervisionado.
• Experiência com versionamento de código (ex.: Git) e práticas de desenvolvimento de software.
• Noções de deployment e monitoramento de modelos.

Diferenciais:

• Experiência prática com MLOps e ferramentas de automação de pipelines (ex.: MLflow, Kubeflow, Airflow).
• Conhecimento em computação em nuvem (AWS, Azure ou GCP), especialmente serviços de IA/ML.
• Experiência com containers e orquestração (ex.: Docker, Kubernetes).
• Implementação de soluções de machine learning em ambientes de produção com requisitos de escalabilidade e segurança.
• Participação em projetos que envolvam modelos de NLP, visão computacional ou sistemas de recomendação.

Perfil profissional:

• Mentalidade analítica e orientação para a resolução de problemas complexos com pragmatismo.
• Proatividade na busca de soluções e na melhoria contínua de processos e modelos.
• Colaboração ativa com diferentes áreas e habilidades de comunicação clara, tanto para públicos técnicos quanto não técnicos.
• Organização, responsabilidade e atenção aos detalhes na entrega de soluções robustas e seguras.
• Interesse por aprendizado contínuo e atualização em relação às tendências e inovações em machine learning.

Se você se identifica com essa oportunidade, inscreva-se! Nosso processo valoriza competências, potencial e diversidade de experiências.