TL;DR

ML Ops Engineer Specialist (AI Engineering): Design and implement robust infrastructure to enable scalable, reliable, and reproducible machine learning workflows with an accent on versioning, training, testing, and deployment of machine learning models across a variety of environments. Focus on continuous integration, model monitoring, auto-scaling, and failover.

Location: Must be based in Brazil

Salary: $30+ per hour

Company

%hirify_global%, by Invisible, is looking for a ML Ops Engineer Specialist.

What you will do

Build scalable ML infrastructure to support versioning, training, testing, and deployment of machine learning models.
Work closely with ML researchers, data scientists, and backend engineers to create efficient, production-ready services and APIs.
Implement systems for continuous integration, model monitoring, auto-scaling, and failover, with a strong emphasis on observability and operational excellence.
Optimize compute resources across cloud and hybrid environments, reducing latency and cost while maintaining high reliability.
Document best practices in MLOps methodologies, including model versioning, reproducibility, metadata tracking, and experiment lineage.

Requirements

2+ years of experience building and maintaining ML infrastructure or platforms in production environments.
Demonstrated ability to take ML models from experimentation to deployment using MLOps best practices.
Experience collaborating with data scientists, ML engineers, and backend teams on cross-functional projects.
Proficiency in Python and core ML tooling (e.g., MLflow, Kubeflow, Airflow, Docker, Git).
Familiarity with model training frameworks such as PyTorch, ONNX, or scikit-learn.
Experience with CI/CD pipelines tailored to ML systems (e.g., model validation checks, artifact versioning).

Nice to have

Hands-on experience with Databricks or similar distributed compute environments.
Familiarity with data engineering tools and workflow orchestration (Spark, dbt, Prefect).
Knowledge of monitoring and observability stacks (Prometheus, Grafana, OpenTelemetry) for ML systems.
Exposure to regulatory/compliance-aware ML deployment (audit logs, reproducibility, rollback strategies).

Culture & Benefits

Independent consultants & contractors who run/operate their own business are welcome.
As a contractor you’ll supply a secure computer and high‑speed internet.
Company‑sponsored benefits such as health insurance and PTO do not apply.

Hiring process

All candidates must pass an interview as part of the contracting process.
The exact rate is determined after evaluating your experience, expertise, and geographic location.
Final offer amounts may vary from the pay range listed above.

Ml Ops Engineer Specialist (Ai Engineering)