Machine Learning Engineer | All LATAM countries | Fully Remote

Halo believes in innovation by inclusion to solve digital problems. As an international agency of over 200 people specializing in interactive media strategy and development, we embrace equity and empowerment in a serious way. Our interdisciplinary teams of unique designers, developers and entrepreneurial minds with a variety of backgrounds, viewpoints, and skills connect to solve business challenges of every shape and size. We empathize to form deep, meaningful relationships with our clients so they can do the same with their audience. Working at Halo feels like belonging. Learn more about our philosophy, benefits, and team at https://halopowered.com/

We are looking for a Machine Learning Engineer to build, optimize, and deploy ML models in production. The ideal candidate has strong Python skills, experience with ML frameworks, and a good understanding of model deployment.

Key Responsibilities

• Develop and optimize machine learning models for real-world applications.
• Work with datasets to preprocess, clean, and engineer features.
• Implement and fine-tune deep learning models (CNNs, RNNs, transformers).
• Deploy ML models using APIs, microservices, or serverless architectures.
• Monitor and maintain deployed models, ensuring performance over time.
• Collaborate with software engineers and data teams to integrate ML solutions.

Requirements

• Python (Pandas, NumPy, Scikit-Learn, TensorFlow/PyTorch).
• Strong knowledge of ML algorithms (supervised, unsupervised, reinforcement learning).
• Experience with feature engineering and model evaluation.
• Familiarity with MLOps tools (Kubeflow, MLflow, Docker, CI/CD for ML).
• Experience with cloud platforms (AWS, GCP, or Azure) for model deployment.

Nice to Have

• Experience with Node.js and JavaScript frameworks (Express, NestJS).
• Knowledge of MongoDB and general database design for ML applications.
• Understanding of full-stack development to integrate ML models into applications.

Benefits

• 100% Remote Work.
• Salary in USD!
• Get to work on challenging projects for the U.S!