Machine Learning Engineer (Recommender Systems)

Factored is seeking a Machine Learning Engineer who will design and implement recommender systems to improve product discovery and enhance customer engagement. The ideal candidate will have experience with large-scale data processing, machine learning libraries, and deep learning techniques.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field.
• 5+ years of proven experience as a Machine Learning Engineer, demonstrating successful development and deployment of Machine Learning models.
• Minimum 1 year of hands-on experience designing, building, and deploying recommender systems.
• Strong programming skills in languages such as Python along with experience with machine learning libraries/frameworks like TensorFlow, PyTorch, or scikit-learn.
• Solid understanding and application of machine learning techniques relevant to recommendation systems, including but not limited to Wide & Deep models, Two-Tower models, Transformers, embeddings, neural networks, autoencoders (AutoRec), and deep sequential models (GRU4Rec).
• Extensive experience handling large-scale data processing and analysis using Spark/PySpark within Databricks, including its native platform services.
• Solid understanding of machine learning algorithms, deep learning, and statistical modeling techniques.
• Strong knowledge of experimental design, A/B testing, and performance evaluation metrics for machine learning solutions.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization (Docker) is a plus.
• Excellent verbal and written communication skills in English.

Benefits

• Ownership through equity participation.
• Annual company retreat.
• Education bonus for continuous learning.
• Company-wide winter break.
• Paid time off.
• Optional in-person events and meetups.
• Tailored career roadmaps.
• High-performance culture.