Senior MLOps Engineer

Extractta

Senior MLOps Engineer responsible for the full lifecycle of machine learning systems. Involved in developing cloud infrastructure and ensuring best practices in software development.

Posted 7/11/2026full-timeRemote • 🇧🇷 BrazilSeniorWebsite

Tech Stack

Tools & technologies

AirflowAWSAzureDockerGoogle Cloud PlatformJavaKafkaKubernetesPythonRustSparkTerraform

About the role

Key responsibilities & impact

Design, build, and maintain complex, distributed systems for the full machine learning lifecycle (from ingestion to production monitoring);
Implement and evolve our MLOps architecture, including Feature Store concepts, Model Serving, and automated CI/CD pipelines;
Manage and apply cloud infrastructure for the team's projects using Infrastructure as Code (IaC) practices;
Develop internal tools and frameworks to optimize the team's workflows;
Ensure adoption of software engineering best practices (testing, clean code, sustainable architecture);
Collaborate with business areas (Product, Customer Success, and Sales/Marketing) to translate commercial needs into viable technical solutions.

Requirements

What you’ll need

Strong experience as a Machine Learning Engineer (MLE) or MLOps Engineer in production environments;
Required knowledge of Distributed Systems and scalable architectures;
Advanced proficiency in Python and solid software engineering practices;
Hands-on experience with large-scale or parallel processing tools such as Spark and/or Dask;
Experience with cloud computing (primary stack: AWS, but knowledge of GCP or Azure is also accepted);
Practical experience managing infrastructure with Terraform;
Experience with containerization (Docker);
Familiarity with the model lifecycle and deployment of traditional models (regression and classification).
Desired:
Hands-on experience with Kubernetes (K8s);
Experience with messaging/streaming systems (Kafka) and asynchronous processing patterns;
Knowledge of workflow orchestration tools, preferably Prefect (Airflow, Kubeflow, or similar also acceptable);
Interest or initial experience in productionizing LLMs / Generative AI;
Knowledge of other languages for system maintenance or performance/data-flow optimization (such as Java, Rust, C/C++ or GPU computing);
Advanced English (reading, writing, and technical documentation).

Benefits

Comp & perks

Meal and/or food allowance
Corporate agreements with Sesi and Sesc, providing access to health, wellness, and leisure services
Partnerships with educational institutions offering exclusive discounts on courses and educational programs
Opportunities for growth within the company and participation in strategic projects
Opportunity to work at a fast-growing company in the market.

ATS Keywords

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonDistributed SystemsSparkDaskTerraformDockerKubernetesKafkaWorkflow Orchestration (Prefect)Model Lifecycle Management