.Who we are:Factored was conceived in Palo Alto, California by Andrew Ng and a team of highly experienced AI researchers, educators, and engineers to help address the significant shortage of qualified AI & Machine-Learning engineers globally.
We know that exceptional technical aptitude, intelligence, communication skills, and passion are equally distributed worldwide, and we are very committed to testing, vetting, and nurturing the most talented engineers for our program and on behalf of our clients.We are seeking a Machine Learning Engineer who is passionate about building state-of-the-art recommender systems and leveraging Generative AI.
You'll work with large-scale data using tools like Databricks and Spark, contributing to innovative AI solutions that enhance personalized experiences while being part of a supportive, dynamic, and collaborative team.
In return, you will be rewarded with an amazing team that supports you, a rich culture, shared success, and the flexibility to work– from the comfort of your home.
#LI-RemoteWhat you will be doing: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.What you must bring: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.Experience with cloud platforms (e.G., AWS, Azure, GCP) and containerization (Docker) is a plus.Excellent verbal and written communication skills in English