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Senior Machine Learning Engineer (Recommender Systems)

3 weeks, 4 days ago
Latin America
Full-time
Senior
Machine Learning Engineer
Software Development
Apache Spark AWS Azure Databricks Deep Learning Docker Feature Engineering GCP Generative AI Machine Learning Neural Networks Python PyTorch Scikit-learn TensorFlow
Apply Now
Factored

Factored

Factored AI provides top AI engineers and solutions for businesses, specializing in business analytics and data science to drive innovation and success.

Internet Software & Services
51-250
Founded 2019
View All Jobs 9

Description

  • Design and implement recommender systems that improve product discovery and customer engagement across digital and physical platforms.
  • Build and manage scalable pipelines for data processing, feature engineering, model training, and deployment using Databricks and Spark.
  • Develop and optimize recommendation models, including Wide & Deep, Two-Tower, Transformer-based, embeddings-based, neural network, autoencoder, and deep sequential architectures.
  • Collaborate with software engineers, data scientists, and business stakeholders to integrate models into production systems.
  • Monitor, maintain, and improve deployed models for reliability, accuracy, and changing business requirements.
  • Apply Generative AI and emerging machine learning techniques to drive innovation.
  • Stay current with 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.
  • 5+ years of experience as a Machine Learning Engineer developing and deploying machine learning models.
  • At least 1 year of hands-on experience designing, building, and deploying recommender systems.
  • Strong Python programming skills and experience with TensorFlow, PyTorch, or scikit-learn.
  • Experience with recommendation techniques including Wide & Deep, Two-Tower, Transformers, embeddings, neural networks, AutoRec, and GRU4Rec.
  • Extensive experience processing and analyzing large-scale data with Spark/PySpark and Databricks native services.
  • Strong understanding of machine learning algorithms, deep learning, and statistical modeling.
  • Knowledge of experimental design, A/B testing, and machine learning performance metrics.
  • Excellent written and verbal English communication skills.
  • Experience with AWS, Azure, or GCP and Docker is preferred.

Benefits

  • Fully remote work environment.
  • Equity participation.
  • Annual company retreat.
  • Education bonus for continuous learning.
  • Company-wide winter break and paid time off.
  • Optional in-person events and meetups.
  • Tailored career roadmaps and professional growth support.

Interested in this position?

Apply directly on the company website

Apply Now

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