Senior Machine Learning Engineer / Tech Lead - Ai & Ml

Jobgether; Brasil; Remote; BRL 240,000 - 540,000; Full time

Benefits offered by this job

Fully remote work environment

Four-day work week

Unlimited paid time off

Job summary

Jobgether procura um Senior Machine Learning Engineer / Tech Lead para liderar soluções de ML em uma plataforma em nuvem, com atuação prática e liderança técnica. O papel envolve trabalhar com ML, infraestrutura de nuvem, Kubernetes e virtualização, promovendo excelência em engenharia.

O candidato ideal tem 4+ anos em ML, experiência com pipelines, MLOps e desenho de arquiteturas em produção, além de competência para atuar com times distribuídos e trabalhar remotamente, com foco em soluções

Qualifications

• 4+ anos de experiência profissional desenvolvendo, implantando e otimizando soluções de ML.
• 2+ anos operando grandes aplicações em produção.
• Experiência com Docker e Kubernetes em produção.

Responsibilities

• Liderar o design, desenvolvimento e otimização de capacidades de ML em plataforma cloud.
• Construir, implantar e otimizar soluções de ML em diferentes modalities.
• Garantir qualidade de código, desempenho e manutenibilidade com melhores práticas.
• Colaborar com PMs, designers e times de engenharia para transformar requisitos em soluções técnicas.
• Melhorar processos de engenharia com documentação, refatoração e práticas recomendadas.
• Mentorar engenheiros e apoiar uma cultura de engenharia de alto desempenho.
• Gerenciar pipelines e workflows de ML seguindo princípios de MLOps.
• Suportar escalabilidade de deployments GPU e clusters de ML.

Skills

Docker

Kubernetes

MLOps

GPU clusters

Cloud infrastructure

Distributed teams

Education

Bacharelado em Ciência da Computação/Engenharia ou equivalente

Tools

Docker

Kubernetes

Job description

Empresa : Jobgether Tipo de Emprego : Periodo Integral Brazil

Senior Machine Learning Engineer / Tech Lead - AI & ML

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Machine Learning Engineer / Tech Lead - AI & ML based in Brazil.

This role offers the opportunity to shape the future of cloud-based machine learning solutions within an innovative engineering environment. You will lead the development of scalable AI capabilities while working across machine learning, cloud infrastructure, Kubernetes, and virtualization technologies. The position combines hands-on engineering with technical leadership, giving you ownership over impactful products and complex systems. You will collaborate with talented global teams to design, deploy, and optimize machine learning solutions used by developers and businesses worldwide. This is an opportunity for an experienced ML engineer who enjoys solving challenging technical problems and building reliable platforms at scale. You will contribute to engineering excellence, open-source initiatives, and the continuous improvement of next-generation AI infrastructure.

Accountabilities

As a Senior Machine Learning Engineer / Tech Lead, you will lead the design, development, and optimization of machine learning capabilities within a cloud platform. You will combine technical expertise, leadership, and collaboration skills to deliver reliable, scalable, and high-performing AI solutions.

• Lead the development and maintenance of scalable and efficient machine learning components within cloud-based platforms.
• Design, build, deploy, and optimize machine learning solutions across different modalities.
• Ensure code quality, reliability, performance, and maintainability through testing, optimization, and engineering best practices.
• Collaborate with product managers, designers, and engineering teams to transform business requirements into effective technical solutions.
• Improve engineering processes through documentation, refactoring, optimization, and implementation of best practices.
• Participate in code reviews and provide constructive feedback to support a strong engineering culture.
• Troubleshoot and resolve complex technical issues across machine learning systems and infrastructure.
• Design and manage machine learning pipelines and workflows following MLOps principles.
• Support the scaling and reliability of GPU-based machine learning deployments and clusters.
• Stay current with emerging machine learning technologies, frameworks, and industry trends.
• Mentor engineers and contribute to improving team performance through technical leadership.

Requirements

The ideal candidate is an experienced machine learning engineer with strong software engineering foundations and proven experience building production-scale AI systems. You should be comfortable working across machine learning, cloud infrastructure, and technical leadership responsibilities.

• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent professional experience.
• 4+ years of professional experience developing, deploying, and optimizing machine learning solutions.
• 2+ years of experience operating large-scale applications and systems in production environments.
• Proven experience training machine learning models across different data modalities.
• Experience designing and building machine learning pipelines, workflows, and MLOps processes.
• Strong experience with containerization technologies such as Docker and Kubernetes.
• Experience managing complex Kubernetes deployments and cloud-native architectures.
• Experience scaling GPU-based machine learning workloads and managing GPU clusters.
• Strong software engineering skills with experience leading complex development projects.
• Excellent written and verbal communication skills.
• Ability to collaborate effectively within distributed and remote engineering teams.

Nice to have

• Experience in software engineering management or technical leadership roles.
• Familiarity with machine learning monitoring and observability tools.
• Experience establishing coding standards, engineering practices, and quality processes.
• Experience working in asynchronous agile environments.
• Contributions to open-source projects and industry initiatives.
• Experience working in fully remote organizations.

Benefits

• Competitive compensation and benefits package.
• Fully remote work environment with a globally distributed team.
• Four-day work week culture, except when attending relevant events.
• Unlimited paid time off policy.
• Opportunity to work on innovative cloud and machine learning technologies.
• Exposure to cutting-edge AI, Kubernetes, virtualization, and cloud computing projects.
• Collaborative and inclusive culture focused on creativity, diversity, and continuous improvement.
• Opportunities to contribute to open-source projects and industry initiatives.
• Strong ownership and impact within a fast-growing technology environment.