Machine Learning / AI Engineer

Machine Learning / AI Engineer (Remote)

Location: Remote (Latin America)

Compensation: $5,500 – $7,500 USD/month

Schedule: Monday – Friday, 9 AM – 6 PM CT (40 hours/week)

Type: Full-time · Independent Contractor

About the Company

Our client is a funded AI-native startup that builds products on top of machine learning and large language models. They ship real AI features to production and need engineers who can take models from prototype to reliable, scalable systems.

About the Role

You build and ship machine learning and AI features in production. You work with data, train or integrate models, build the pipelines around them, and make sure they run reliably at scale. Some weeks you are building retrieval over a large language model; others you are hardening an inference pipeline. This role fits someone who ships reliable systems, not just prototypes.

Key Responsibilities

• Build, train, fine-tune, or integrate machine learning and large language model features.
• Design and own the data and inference pipelines that put models into production.
• Evaluate model quality and improve accuracy, latency, and cost.
• Work with product and engineering to ship AI features end to end.
• Monitor models in production and fix drift, errors, and bottlenecks.
• Stay current with the AI tooling landscape and apply what is useful. Who You Are
• You have 3+ years building machine learning or AI systems, with work that reached production.
• You are strong in Python and the modern AI stack (large language model APIs, retrieval, frameworks such as LangChain, vector databases).
• You understand data pipelines, evaluation, and the engineering around models, not just notebooks.
• Your English is excellent in speech and writing; you work comfortably with a US team.
• You ship reliable systems and take ownership of what you build. Bonus Points
• Experience with fine-tuning, retrieval-augmented generation, or agent systems in production.
• Cloud and MLOps experience (AWS, GCP, containers, pipelines).
• Degree in computer science, data, or a related field. What Success Looks Like

First 90 Days

• You understand the current ML architecture, data pipelines, and production models.
• You have shipped one feature or hardened one pipeline end to end.
• You are trusted to own a model or pipeline without constant review. Ongoing
• You regularly ship AI features that improve product and reach users.
• Models you own stay reliable in production with minimal drift or errors.
• You improve accuracy, latency, or cost on at least one system per quarter. How to Apply

Submit your resume in PDF format and complete the short skills assessment we share with every applicant. The assessment is how we evaluate written communication, accuracy, and attention to detail for this role.

What to Expect

• Application Review: We review your resume and assessment results.
• WhatsApp Screen: A brief introductory conversation.
• Recruiter Interview: A deeper conversation to assess fit and working style.
• Client Interview: You meet the hiring manager directly.
• Background Check + Offer: Final verification followed by your offer letter.