Description:

ReflexAI is seeking a Machine Learning Operations Engineer to join their team, reporting to the Head of AI.
This is a full-time remote position based in Latin America with a compensation range of $45,000 - $75,000 base salary plus equity.
The role involves working on large-scale projects to build, iterate, and maintain the ML platform, which is designed to accelerate the development, deployment, and maintenance of ML models.
Responsibilities include designing and implementing improvements to the ML platform, collaborating with cross-functional teams, setting standards for machine learning workflows, implementing CI/CD for ML models, and expanding the data warehouse with new data sources and dashboards.

Requirements:

Candidates should have significant experience, typically 3+ years, in ML or ML Ops within a production environment.
Experience in building end-to-end scalable ML infrastructure and data pipelines using cloud platforms such as Google Cloud Platform (GCP), Amazon Web Services (AWS), or Azure is required.
Candidates must have experience with container-based deployments, such as Docker and Kubernetes.
Experience in developing machine learning models and LLM applications is considered a plus.
Candidates should have experience in building ML systems with robust logging, monitoring, and alerting systems, as well as load testing systems to support scalable ML Ops.
Proficiency in Python, Terraform, and data warehousing languages and tools (SQL, dbt, BigQuery, Fivetran, etc.) is necessary.
Strong teamwork skills, including effective communication and collaboration with both technical and non-technical team members, are essential.
Candidates should demonstrate open-mindedness, professionalism, empathy, and a strong desire to learn.

ReflexAI offers generous retirement, equity, healthcare, and paid time off (PTO) policies.
Employees have the flexibility to work remotely from anywhere in Latin America.
ReflexAI is committed to being an equal opportunity employer, ensuring equal employment opportunity regardless of various protected classes.