Senior Machine Learning Engineer (Recommender Systems)

Location: Latin America; fully remote

Company

hirify.global helps U.S. companies build and scale AI, machine learning, and data teams with talent from Latin America.

What you will do

• Design and implement recommender systems that improve product discovery and customer engagement across digital and physical platforms.
• Build scalable machine learning pipelines for data processing, feature engineering, model training, and deployment using Databricks and Spark.
• Apply and optimize Wide & Deep, Two-Tower, Transformer-based, embeddings-based, neural network, autoencoder, and deep sequential recommendation models.
• Collaborate with software engineers, data scientists, and business stakeholders to integrate models into production systems.
• Monitor, maintain, and continuously improve deployed models for reliability, accuracy, and alignment with business needs.
• Track advances in machine learning, recommender systems, deep learning, and Generative AI.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field.
• At least 5 years of experience developing and deploying machine learning models.
• At least 1 year of hands-on experience designing, building, and deploying recommender systems is required.
• Strong Python programming skills and experience with TensorFlow, PyTorch, or scikit-learn.
• Experience processing and analyzing large-scale data with Spark or PySpark in Databricks, including native platform services.
• Strong understanding of machine learning algorithms, deep learning, statistical modeling, experimental design, A/B testing, and evaluation metrics; excellent English communication skills are required.

Nice to have

• Experience with AWS, Azure, or GCP.
• Experience with Docker and containerization.

Culture & Benefits

• Remote work from home with optional in-person events and meetups.
• Equity participation and a company-wide winter break.
• Paid time off, an annual company retreat, and an education bonus.
• Tailored career roadmaps and support for continuous professional growth.
• Transparent, collaborative, learning-focused, and high-performance environment.