Apollo.io is hiring a
Senior Machine Learning Engineer

Summary

Apollo.io is a leading go-to-market solution for revenue teams with over 500,000 companies using its platform. As a Senior Machine Learning Engineer on the Intelligence team, you will build and productionize ML models and algorithms to personalize users' experiences and optimize their journey. Apollo.io is a remote-first inclusive organization with a focus on operational excellence.

Requirements

• Bachelors, Masters, or a PhD in Computer Science, Mathematics, Statistics, or other quantitative fields or related work experience
• 6+ years of experience building Machine Learning or AI systems
• Experience deploying and managing machine learning models in the cloud
• Strong analytical and problem-solving skills
• Proven software engineering skills in production environment, primarily using Python
• Experience with Machine Learning software tools and libraries (e.g., Scikit-learn, TensorFlow, Keras, PyTorch, etc.)

Responsibilities

• Design, build, evaluate, deploy and iterate on scalable Machine Learning systems
• Understand the Machine Learning stack at Apollo and continuously improve it
• Build systems that help Apollo personalize their users’ experience
• Evaluate the performance of machine learning systems against business objectives
• Develop and maintain scalable data pipelines that power our algorithms
• Implement automated monitoring, alerting, self-healing (restartable/graceful failures) features while productionizing data & ML workflows
• Write unit/integration tests and contribute to engineering wiki

Preferred Qualifications

• PhD in Computer Science or related field with a focus on machine learning
• Experience with Databricks, Google Cloud Platform, Snowflake, mlflow, and Airflow
• Experience with one or more of the following: natural language processing, deep learning, recommendation systems, search relevance & ranking, and speech-to-text conversion

Benefits

• Great compensation package
• Culture that thrives in openness and excellence
• Investment in developing remote employees’ careers
• Collaborative environment with support from teammates and departments
• Empowerment to experiment and take educated risks that lead to big wins