Machine Learning Engineer

About Promtior

Promtior is at the forefront of the Agentic AI revolution, delivering cutting-edge solutions that transform businesses across industries — bridging technology and people to turn AI into a real competitive advantage. Since 2023, we've helped organizations boost operational efficiency through tailored Agentic AI solutions, from discovery and development to full implementation, across three core lines: AI Product Delivery (predictive analytics, intelligent automation, AI-driven chatbots, image processing), AI Department as a Service (LATAM-based teams that integrate directly with our clients' teams), and AI Adoption Consulting (helping companies find and act on AI opportunities across their business).
We're a team held together by genuine relationships, constant exchange, and shared learning. We believe innovation happens when people feel included and collaborate with purpose, and we aim for professional growth to go hand in hand with personal well-being.

About the Role

We're looking for a Machine Learning Engineer to join our Engineering team and help power our global growth.

Key Responsibilities

You will design, develop, and deploy machine learning models in production environments. You will work with complex datasets, handling processing, cleaning, and feature engineering, and train, evaluate, and optimize supervised and unsupervised models. You will implement training, validation, and model serving pipelines, collaborating with product and engineering teams to integrate models into real applications. You will participate in the design of scalable data and ML system architectures, monitor model performance in production, and propose continuous improvements. You will implement MLOps best practices (versioning, testing, deployment, monitoring), and use AI tools to accelerate development, experimentation, and analysis.

Required Experience

• Hands-on experience developing and productionizing machine learning models.

• Strong command of Python and ML libraries (scikit-learn, TensorFlow, PyTorch, or others).

• Experience working with data (ETL, analysis, feature engineering).

• Experience deploying models in cloud environments (AWS, GCP, or Azure).

• Knowledge of APIs, backend, or service integration.

• Experience working with data and/or ML pipelines.

• Good command of Git and collaborative work in technical teams.

• Advanced English Level.

Especially Valued

• Experience with NLP or computer vision models.

• Experience in generative AI (LLMs, embeddings, RAG).

• Knowledge of MLOps (MLflow, Kubeflow, SageMaker, or others).

• Experience with distributed processing (Spark, Ray, or others).

• Experience in model optimization and hyperparameter tuning.

• Knowledge of data engineering or data architecture.

• Experience working in production environments with high data volume.

• Technical curiosity and eagerness to learn new AI technologies.

Benefits

• 20 paid days off per year.

• Hybrid work model.

• Flex Days: monthly team activities.

• Professional development courses.

• Internal clubs (soccer, padel, running, cinema).

Location

Montevideo, Uruguay.
Córdoba, Corrientes or Chaco, Argentina.

· Hybrid work arrangement