Machine Learning Engineer

Brisk Dev; Colombia; Remote; COP 295,975,000 - 460,405,000; Full time

Job summary

Brisk Dev is seeking a Data & AI Engineer to design, train, and deploy machine learning models for production use cases in a remote Americas setting. You will build robust data pipelines, own model serving infrastructure, and monitor for drift in production.

The role requires 4+ years shipping ML systems to production, strong Python programming with PyTorch and scikit-learn, and a solid grasp of MLOps, versioning, monitoring, and reproducibility.

Qualifications

• 4+ years shipping ML systems to production.
• Strong Python, with experience in PyTorch, scikit-learn, or comparable tooling.
• Solid grasp of MLOps practices, versioning, monitoring, and reproducibility.
• Able to explain model behavior and limitations to non-technical stakeholders.

Responsibilities

• Design, train, and deploy models for classification, ranking, or applied LLM use cases.
• Build robust data pipelines and evaluation harnesses that catch regressions before clients do.
• Own model serving infrastructure and monitor for drift in production.
• Translate ambiguous business problems into scoped, measurable ML work.

Skills

Python

PyTorch

Scikit-learn

MLOps

Model Monitoring

Explainability

Tools

PyTorch

Scikit-learn

Job description

Data & AI Remote, Americas Full-time 4+ years

What you'll do

• Design, train, and deploy models for classification, ranking, or applied LLM use cases.
• Build robust data pipelines and evaluation harnesses that catch regressions before clients do.
• Own model serving infrastructure and monitor for drift in production.
• Translate ambiguous business problems into scoped, measurable ML work.

What we're looking for

• 4+ years shipping machine learning systems to production, not just research.
• Strong Python, with experience in PyTorch, scikit-learn, or comparable tooling.
• Solid grasp of MLOps practices, versioning, monitoring, and reproducibility.
• Able to explain model behavior and limitations to non-technical stakeholders.

Nice to have

Experience fine-tuning or evaluating LLMs Familiarity with vector databases Published research or blog writing