As a Senior Machine Learning Engineer on the Intelligence team, you will be responsible for building and productionizing Machine Learning (ML) models and other smart algorithms for various Apollo.io products. These products may include Search, Recommendations, Content generation, Conversations, or similar. The mission of the Intelligence team is to leverage Apollo's massive scale data to understand and predict Apollo users' behaviors and optimize their experience at all stages of their product journey. 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, and self-healing (restartable/graceful failures) features while productionizing data and ML workflows. Write unit/integration tests and contribute to the engineering wiki. Requirements: Bachelor's, Master's, 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. Experience working with fine-tuning LLMs and prompt engineering. Strong analytical and problem-solving skills. Proven software engineering skills in a production environment, primarily using Python. Experience with Machine Learning software tools and libraries (e. g., Scikit-learn, TensorFlow, Keras, PyTorch, etc. ). Competencies: Documentation first approach; loves to scale up by writing things down to share knowledge asynchronously. Excellent communication skills; be able to work with stakeholders to develop and define key business questions and build data sets that answer those questions. Excellent ambiguity resolution skills; be able to break down ambiguous problems into simpler milestones and delegate to junior engineers. Self-motivated and self-directed. Inquisitive, able to ask questions and dig deeper. Organized, diligent, and with great attention to detail. Acts with the utmost integrity. Genuinely curious and open; loves learning. Critical thinking and proven problem-solving skills are required. 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 and ranking, and speech-to-text conversion.

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