We're looking for a Semi-Senior Machine Learning Engineer 🤖
About the Role
We are looking for a Semi-Senior Machine Learning Engineer to join our team and work on challenging, high-impact ML and AI systems. This is a hybrid position based in Montevideo, Uruguay.
You'll contribute across the ML lifecycle — from experimentation and model development to deployment and monitoring in production — with support and mentorship from senior engineers. If you enjoy working at the intersection of deep learning and modern LLM-powered systems, and you care about shipping things that actually work, this role is for you.
What You'll Do
- Develop and help deploy machine learning models and AI-powered features into production systems.
- Build and maintain ML pipelines — data ingestion, feature engineering, training, evaluation, and serving.
- Work with LLMs to solve real-world problems, including prompt engineering, RAG architectures, and integration with orchestration frameworks like LangGraph, PydanticAI, or OpenAI Agents.
- Collaborate with backend and data engineering teams to integrate ML solutions into existing infrastructure.
- Help monitor and maintain models in production, supporting reliability and performance over time.
- Contribute to MLOps practices: experiment tracking, model versioning, and CI/CD for ML.
What We're Looking For
- 2+ years of professional experience in Machine Learning or AI engineering roles.
- Solid foundations in ML — supervised/unsupervised learning, model evaluation, feature engineering.
- Some hands-on experience building or shipping ML systems in production environments.
- Proficiency in Python and familiarity with at least one deep learning framework (PyTorch preferred).
- Exposure to LLMs — whether through RAG, fine-tuning, or building LLM-powered applications.
- Familiarity with cloud platforms and ML tooling (AWS a plus).
- Familiarity with containerization (Docker) and software engineering best practices (testing, versioning, CI/CD).
- Good communication skills and solid English proficiency (written and spoken) — you'll be working with English-speaking stakeholders.
Nice to Have
- Experience building or consuming APIs using FastAPI, Flask, or Django.
- Experience with vector databases (Qdrant, Chroma, OpenSearch, pgvector) and semantic search.
- Background in NLP, information retrieval, or recommendation systems.
- Familiarity with model evaluation frameworks and responsible AI practices.
- Interest in keeping up with the latest ML and AI research.