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TI e programação

Engineering Manager - MLOps & Analytics - vaga remota

Canonical Ltd.

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Publicada: (ontem)Ativa até: até 1 de outubro de 2026

Engineering Manager - MLOps & Analytics - TI e programação, remoto

A empresa Canonical Ltd. está com uma vaga aberta de Engineering Manager - MLOps & Analytics: nível de liderança, com responsabilidade sobre uma equipe ou sobre uma área inteira. A posição fica na área de TI e programação e é totalmente remota. A empresa não impõe restrição sobre onde o candidato mora, então você pode se candidatar de onde estiver.

As principais ferramentas citadas no anúncio são: Python, Machine Learning. O currículo precisa mostrar exemplos concretos exatamente dessas habilidades.

A empresa não publicou nenhum valor, isso é acertado na entrevista. O anúncio não impõe condição nenhuma de horário.

Esta vaga passou por uma verificação automática: anúncios que exigem autorização de trabalho estrangeira, patrocínio de visto, uma nacionalidade específica ou residência em um país indicado não entram na lista.

Em resumo

Empresa
Canonical Ltd.
Área
TI e programação
Quem pode se candidatar
De qualquer país do mundo
Formato de trabalho
Totalmente remota
Nível
Liderança
Ferramentas
Python, Machine Learning
Tipo de contrato
Tempo integral
Publicada
22 de agosto de 2026 (ontem)
Ativa
até 1 de outubro de 2026
Fonte
Jobicy

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Descrição da empresa

The role of an Engineering Manager at Canonical As an Engineering Manager at Canonical, you must be technically strong, but your main responsibility is to run an effective team and develop the colleagues you manage. You will develop and review code as a leader, while at the same time staying aware of that the best way to improve the product is to ensure that the whole team is focused, productive and unblocked. You are expected to help them grow as engineers, do meaningful work, do it outstandingly well, find professional and personal satisfaction, and work well with colleagues and the community. You will also be expected to be a positive influence on culture, facilitate technical delivery, and regularly reflect with your team on strategy and execution. You will collaborate closely with other Engineering Managers, product managers, and architects, producing an engineering roadmap with ambitious and achievable goals. We expect Engineering Managers to be fluent in the programming language, architecture, and components that their team uses, in this case popular open-source machine learning tools like Kubeflow, MLFlow, and Feast. Code reviews and architectural leadership are part of the job. The commitment to healthy engineering practices, documentation, quality and performance optimisation is as important, as is the requirement for fair and clear management, and the obligation to ensure a high-performing team. Location: This is a Globally remote role.

What your day will look like

* Manage a distributed team of engineers and its MLOps/Analytics portfolio

* Organize and lead the team’s processes in order to help it achieve its objectives

* Conduct one-on-one meetings with team members

* Identify and measure team health indicators

* Interact with a vibrant community

* Review code produced by other engineers

* Attend conferences to represent Canonical and its MLOps solutions

* Mentor and grow your direct reports, helping them achieve their professional goals

* Work from home with global travel for 2 to 4 weeks per year for internal and external events

What we are looking for in you

* A proven track record of professional experience of software delivery

* Professional python development experience, preferably with a track record in open source

* A proven understanding of the machine learning space, its challenges and opportunities to improve

* Experience designing and implementing MLOps solutions

* An exceptional academic track record from both high school and preferably university

* Willingness to travel up to 4 times a year for internal events

Additional skills that you might also bring The following skills may be helpful to you in the role, but we don't expect everyone to bring all of them.

* Hands-on experience with machine learning libraries, or tools.

* Proven track record of building highly automated machine learning solutions for the cloud.

* Experience with building machine learning models

* Experience with container technologies (Docker, LXD, Kubernetes, etc.)

* Experience with public clouds (AWS, Azure, Google Cloud)

* Experience in the Linux and open-source software world

* Working knowledge of cloud computing

* Passionate about software quality and testing

* Experience working on a distributed team on an open source project -- even if that is community open source contributions.

* Demonstrated track record of Open Source contributions

What we offer you We consider geographical location, experience, and performance in shaping compensation worldwide. We revisit compensation annually (and more often for graduates and associates) to ensure we recognise outstanding performance. In addition to base pay, we offer a performance-driven annual bonus. We provide all team members with additional benefits, which reflect our values and ideals. We balance our programs to meet local needs and ensure fairness globally.

* Distributed work environment with twice-yearly team sprints in person - we’ve been working remotely since 2004!

* Personal learning and development budget of USD 2,000 per year

* Annual compensation review

* Recognition rewards

* Annual holiday leave

* Maternity and paternity leave

* Employee Assistance Programme

* Opportunity to travel to new locations to meet colleagues from your team and others

* Priority Pass for travel and travel upgrades for long haul company events

About Canonical Canonical is a pioneering tech firm that is at the forefront of the global move to open source. As the company that publishes Ubuntu, one of the most important open source projects and the platform for AI, IoT and the cloud, we are changing the world on a daily basis. We recruit on a global basis and set a very high standard for people joining the company. We expect excellence - in order to succeed, we need to be the best at what we do. Canonical has been a remote-first company since its inception in 2004.​ Work at Canonical is a step into the future, and will challenge you to think differently, work smarter, learn new skills, and raise your game. Canonical provides a unique window into the world of 21st-century digital business. Canonical is an equal opportunity employer We are proud to foster a workplace free from discrimination. Diversity of experience, perspectives, and background create a better work environment and better products. Whatever your identity, we will give your application fair consideration.

#LI-remote

O texto permanece no idioma original da empresa, porque é nesse mesmo idioma que você vai se candidatar.

Esta vaga foi publicada em Jobicy. Anúncio original (Jobicy)

Perguntas frequentes sobre esta vaga

Posso me candidatar à vaga de Engineering Manager - MLOps & Analytics de onde eu moro?

Sim. Para esta vaga, Canonical Ltd. aceita candidatos de qualquer país do mundo, então você não precisa de autorização de trabalho de outro país. O anúncio passou por uma verificação automática: se a empresa exigisse autorização de trabalho, patrocínio de visto ou residência em um país específico, ele não estaria neste quadro.

Qual é a remuneração informada?

Para esta vaga, Canonical Ltd. não divulgou remuneração. A maioria dos anúncios remotos não publica valor, isso é acertado na entrevista.

Como eu me candidato?

Você se candidata diretamente à empresa, pelo anúncio original publicado em Jobicy. Donator não recebe candidaturas, não cobra comissão e não guarda currículos.

Que tipo de vaga é esta?

Uma vaga totalmente remota na área de TI e programação. Anúncios híbridos e tudo o que exige presença no escritório não são publicados neste quadro.

Certificados gratuitos para esta vaga

Este anúncio pede Python, Machine Learning. Abaixo estão os certificados gratuitos que cobrem exatamente essas ferramentas.

Todos os certificados gratuitos: IT and cloud

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