Machine Learning Engineer

Summary

Join Factored, a company founded by Andrew Ng, as a Machine Learning Engineer. You will design and implement recommender systems, build scalable machine learning pipelines using tools like Databricks and Spark, and collaborate with a team to integrate models into production. This role requires a Bachelor's or Master's degree in a related field, proven experience in developing and deploying recommender systems, and strong programming skills in Python. You will work with large-scale data and leverage various machine learning libraries. The position offers the flexibility to work remotely from home and is part of a supportive and collaborative team. Factored invests in employee growth and offers a rich culture.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field
• Proven experience as a Machine Learning Engineer, demonstrating successful development and deployment of recommender systems
• Strong programming skills in languages such as Python along with experience with machine learning libraries/frameworks like TensorFlow, PyTorch, or scikit-learn
• 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
• Excellent verbal and written communication skills in English

Responsibilities

• Design and implement recommender systems to improve product discovery and enhance customer engagement across digital and physical platforms
• Build and manage scalable machine learning pipelines for data processing, feature engineering, model training, and deployment using tools like Databricks and Spark
• Develop and refine machine learning models to tackle complex problems, leveraging diverse datasets and optimizing performance through parameter tuning and experimentation
• Collaborate with software engineers, data scientists, and business stakeholders to integrate models into production and address key business challenges with machine learning solutions
• Monitor and maintain deployed models, ensuring performance, reliability, and alignment with evolving business needs through continuous improvement practices
• Stay informed on advancements in AI and machine learning, incorporate innovative techniques, and contribute to knowledge-sharing initiatives to improve overall practices

Preferred Qualifications

Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization (Docker)

Benefits

• Flexibility to work– from the comfort of your home
• Amazing team that supports you
• Rich culture
• Shared success
• Invest in you and support your career and professional growth in many meaningful ways