We are an integrated energy player. We contribute not only to the entire oil and gas value chain, but we are also proud to have an active role on the energy paradigm shift, through the expansion of our renewable energy generation businesses. We are the largest Iberian producer of solar energy and the leader of our sector in the main global sustainability indexes.

Working at Galp is about bringing more energy to the world. Is about having the ambition to build the future in a sector that is going through a deep transformation, being even more efficient and sustainable.

We are 4 geographies, 49 nationalities and more than 6.000 experiences waiting to be shared.  We value and encourage our people to boost their progress through continuous improvement and innovation, promoting opportunities in different business areas and geographies.

We are looking for people with strength, passion, determination and vision to be part of our growth. Will you accept the challenge?



MLOps Engineer





We are looking for a Machine Learning Operations (MLOps) Engineer to help in provisions and maintenance of infrastructure, manage configurations, implement CI/CD pipelines for applications and infrastructure, implement testing and monitoring tools and help managing the lifecycle of models and algorithms for the Data Science teams.

This person will use industry standards and best practices to fully automate all environments and deployments and, also, standard tool set (version-control system, continuous build, continuous delivery/deploy, containers, secret engine, artifact service) in fully automated pipeline.

Your ultimate goal is to deploy and maintain data science products and environments. 



What you’ll do


  • Deploy and manage environments for data science, using tools such as docker, kubernets, Airflow, Databricks, kubeflow, etc
  • Support data scientists and analysts by creating and managing environments for data exploration and visualization. Deploy and manage data science development environments to evolve machine learning models using Python, R, Jupyter Notebooks, PyCharm, RStudio, Spark, and Databricks.
  • Provision, configure, scale and manage high performance computing clusters. Create scripts to automate the provisioning and configuration of the infrastructure for a variety of environments.
  • Deploy sophisticated CI/CD pipelines to bridge the gap between ML training environments and model deployment environments
  • Build and maintain CI/CD pipeline with the following tools (e.g. Jira, github, Docker, Kubernetes, Python,
  • Build REST APIs to serving ML models
  • Host machine learning models as microservices in a scalable environment using containers and container management tools.
  • Improve model tracking, versioning, monitoring and management (ex. MLFlow)
  • Create a cyclical lifecycle for the modern ML model.
  • Standardize the machine learning process to meet regulatory standards and policies.
  • Design and build systems which improve scalability, usability, and performance.
  • Work cross-functionally with product managers and engineers to understand, implement, and deploy pipelines.



What you’ll need


  • Bachelor’s Degree in Engineering, Computer Science, or other related discipline
  • Experience as DevOps, Data Engineering, MLOps or similar role
  • Experience with major cloud computing services – AWS and / or Azure
  • Experience with Machine Learning Frameworks, Python, and R
  • Experience with scripting languages Python (2-3 years minimum)
  • Experience with R (1-2 years minimum) and with Shinny Applications (nice to have)
  • Experience with container-based deployment – Kubernetes, Docker, Jenkins (1-2 years minimum)
  • Knowledge of big data tools like Apache spark, Apache Kafka, databricks, Airflow, Kubeflow, etc
  • Knowledge of machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)
  • An analytical mind with problem-solving abilities
  • Good communication skills
  • Passion for building useful things
  • Will to be part of a team of a large organization with a startup spirit
  • Intention to be involved in a technological environment in constant innovation
  • Sharing Spirit
  • Curious and a true team player, with eager to learn something new every day
  • Positive attitude



Deadline for Applications

May, 10th, 2021




Diversity Commitment

At Galp, we promote equality of opportunity and treatment of people regardless of gender, religion or belief, disability, age, sexual orientation, and race. We believe that equality creates value and strengthens a Group culture.

Ingressei na Galp/Petrogal em 2014 e desde então tenho trabalhado com os ativos de Potiguar offshore. No segundo ano de empresa, também me tornei TCR destes ativos e pude compreender um pouco mais além da área técnica. Têm sido anos de intenso aprendizado, com reuniões, horas em frente a estação de trabalho, acompanhamento de poços e por vezes participação de outros projetos, como avaliação de outros activos, o que me deixa muito feliz em ter a possibilidade de ver novas áreas, geologia diferente e talvez a possibilidade de ajudar a empresa a aumentar seu portfólio com boas oportunidades… Concomitantemente, ao meu crescimento profissional, vivenciei a mudança da presidência da empresa, da sede para o Rio de Janeiro, dos valores e da missão. Foram anos de cursos, muito trabalho, aprendizado e acompanhamento para se adequar a nova forma de trabalho. Dentre os pontos positivos de trabalhar na Galp/Petrogal, destaco o bom tratamento com os colaboradores, sempre humanizado e com a compreensão que em certos momentos da vida são necessários, a parceria entre os colegas, reconhecimento do trabalho executado e sólido portfólio. Ainda sobre a relação com os colegas, posso dizer que na maior parte das vezes é colaborativa, sempre há alguém disposto a te ajudar com uma boa ideia ou sentar ao seu lado para discutir um problema de modo a saná-lo.

Patricia Takayama