MLOps Analyst

Babel, the great way to achieve the success.

Do you want to be part of an expanding, committed, and innovative team that makes history every day? At Babel, we accompany you on your path to success. We believe in the talent of people and we want to empower it by offering you a great working environment based on collaboration and solidarity.

Working at Babel is much more than working at a company; it is joining a team of people with a shared mission and a company model centered on values.

And we do this by promoting diversity, equity, and inclusion, guaranteeing equal opportunities to all candidates, in an environment free of any type of discrimination.

Additionally,

• We bet on work-life flexibility. (Point-based vacation system, remote work, and flexibility).

• We invest in the training of our Babelievers.

• We invest in your physical and emotional health. (Private Medical Insurance/ Life insurance, personal trainer, and wellbeing program).

• We also invest in your free time (Nature activities, sports championships, streaming platform subscription (e.g., Netflix))

• We participate in the growth of the company and recognize the participation of each person (Benefits Bonus).

• We focus on working with the latest technologies and innovative projects, but above all, we accompany digital transformation and bring technology closer to society.

Do you accept the challenge? We are waiting for you!

We look toward the future! Our Hyperspace 2029 strategic plan promises to be an exciting journey, full of opportunities to grow and develop professionally. Reaching 1 billion in revenue, a challenge that we are sure that with the collaboration and talent of our people, will be another success story that we will write together.

We are looking for a Senior MLOps Engineer to participate in Artificial Intelligence projects, working on the development, deployment, and maintenance of AI solutions in production environments.

The role combines software engineering, automation, and Machine Learning, collaborating with Data Science, DevOps, and business teams to guarantee scalable, reliable, and efficient solutions.

• Develop and deploy AI/ML applications and models with Python.
• Manage container environments and deployments on Kubernetes.
• Design ETL processes with Python and Spark.
• Develop and integrate APIs for Artificial Intelligence solutions.
• Implement and optimize CI/CD pipelines, automating tests and deployments.
• Monitor applications in production, guaranteeing their performance and stability.
• Collaborate with Data Scientists, Product Owners, and technical teams on the evolution of solutions.