Role: AI Engineer (Machine Learning Engineer)
Priority Location: LATAM
Working Hours: PST (Pacific Standard Time)

This is a full-time remote role working with a U.S.-based team. Candidates must be comfortable with some overlap with U.S. working hours.

Type of contract: Independent Contractor
Type of job: Remote

The final offer is at the client’s discretion and will depend on the candidate’s interview result, skills, and experience.

About the Role

A data-driven marketing technology organization specializing in advanced analytics and optimization solutions. By leveraging machine learning and robust data infrastructure, it drives measurable business impact at scale.

As an AI Engineer (Machine Learning Engineer), you will own and operate machine learning systems in production. This role focuses on production environments, orchestration, and infrastructure rather than pure experimentation.

You will act as a key connector between Data Science, Data Engineering, and AI systems, ensuring models are successfully deployed, integrated, and maintained in real-world applications. This is a hands-on role requiring strong ownership of ML pipelines, system performance, and reliability.

Key Responsibilities

Own and maintain ML pipelines in production environments, including batch and orchestration-heavy workflows
Build and manage end-to-end data and ML pipelines for both training and inference
Orchestrate workflows using tools such as Flyte or similar platforms
Collaborate closely with Data Scientists to productionize machine learning models
Integrate ML and AI components across various systems and services
Ensure system reliability through monitoring, performance optimization, and troubleshooting
Partner with Data Engineers on data infrastructure and pipeline development
Apply best practices in MLOps, documentation, and scalable system design

Qualifications & Skills

Hard Skills:

3–5+ years of experience in Machine Learning Engineering or similar roles
Strong proficiency in Python and SQL
Experience building and maintaining ML pipelines end-to-end
Solid understanding of ML systems, deployment processes, and orchestration
Hands-on experience with MLOps practices
Strong knowledge of infrastructure and system design

Nice to Have:

Experience with Flyte or similar orchestration tools
Exposure to LLMs or AI systems
Experience working with marketing data, attribution models, or forecasting
Familiarity with Kubernetes or cloud environments

Soft Skills:

Strong ownership mindset with the ability to manage projects end-to-end
Cross-functional collaboration skills across Data Science, Engineering, and AI teams
Problem-solving mindset with a focus on system reliability and efficiency
Detail-oriented with a structured and process-driven approach

What’s in it for you?

Full-time, fully remote position
11 US holidays + 3 weeks of paid time off
Performance-based bonus program

AI Engineer - 18586