Machine Learning / AI Engineer

Puente Talent Partners; Argentina; Remote; ARS 1,800,000 - 3,000,000; Full time

Job summary

Puente connects experienced Latin American professionals with growing US companies. We do not operate as a generic job board: we selectively match candidates with active roles and guide them through the hiring process.

You will own ML/AI features from prototype to production, building retrieval over LLMs, tuning pipelines and ensuring reliability, latency and cost. You will work with a US team and deliver real AI features that reach users.

This is a fully remote role with strong growth and impact.

Qualifications

• 3+ years building ML/AI systems with production experience.
• Proficient in Python and modern AI stack (LLMs, retrieval, LangChain).
• Strong data pipelines, evaluation, and model engineering.
• Able to ship reliable systems with ownership.

Responsibilities

• Build, train, fine-tune or integrate ML/LLM features.
• Develop data and inference pipelines for production.
• Evaluate models and improve accuracy, latency, cost.
• Deliver end-to-end AI features with product and engineering.
• Monitor production, fix drift, errors and bottlenecks.
• Stay current with AI tooling and apply useful tech.

Skills

3+ years ML/AI production

Python & AI stack

Data pipelines & eval

Ownership & reliability

English C1 (written)

Education

Degree in CS/Data or related field

Tools

LangChain

Vector databases

LLM APIs

Cloud platforms

Containers

Job description

You build and ship machine learning and AI features in production. Some weeks you are building retrieval over a large language model; others you are hardening an inference pipeline.

Why this role exists

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.

What you'll own

• Machine learning and large language model features: built, trained, fine-tuned or integrated
• The data and inference pipelines that put models into production
• Model evaluation, with improvements to accuracy, latency and cost
• AI features shipped end to end with product and engineering
• Production monitoring, fixing drift, errors and bottlenecks
• Staying current with the AI tooling landscape and applying what is useful

Why this is interesting

• Real AI features that reach users, not just prototypes
• Ownership of models and pipelines in production
• A funded AI-native startup working with large language models, retrieval and agent systems

What we're looking for

• 3+ years building machine learning or AI systems, with work that reached production
• Strong in Python and the modern AI stack (large language model APIs, retrieval, frameworks such as LangChain, vector databases)
• Solid grasp of data pipelines, evaluation and the engineering around models, not just notebooks
• You ship reliable systems and take ownership of what you build
• English C1, written and spoken. You work comfortably with a US team

Bonus

• 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, and you are trusted to own a model or pipeline without constant review.

Ongoing

You regularly ship AI features that improve the product and reach users. Models you own stay reliable in production with minimal drift or errors, and you improve accuracy, latency or cost on at least one system per quarter.

Why Puente

Puente connects experienced Latin American professionals with growing US companies. We do not operate as a generic job board: we selectively match candidates with active roles and guide them through the hiring process.

3% acceptance rate · 2,873+ professionals placed · 97% retention beyond 12 months · 18 countries · 100% remote

Hiring process

• Puente screening: a WhatsApp intro, then a recruiter interview
• Client interview with the hiring manager
• Background check and offer