Staff Machine Learning Engineer

Position Overview

Apollo.io is seeking a Staff Machine Learning Engineer to join our Intelligence team. This role is pivotal in leading mission-critical initiatives that power ML-driven user experiences across search, recommendations, content generation, scoring, and more. You will be instrumental in advancing Apollo as an AI-native product, developing intelligent, personalized, and highly automated features that scale. You will collaborate closely with engineers, product managers, and data scientists to build machine learning systems that enhance user value and drive the future of our AI platform.

About Apollo.io

Apollo.io is the leading go-to-market solution for revenue teams, trusted by over 500,000 companies and millions of users globally. Founded in 2015, Apollo.io is one of the fastest-growing companies in SaaS, raising approximately $250 million to date and valued at $1.6 billion. We provide sales and marketing teams with easy access to verified contact data for over 210 million B2B contacts and 35 million companies worldwide, along with tools to engage and convert these contacts in one unified platform. Apollo raised a Series D in 2023 and is backed by top-tier investors, including Sequoia Capital, Bain Capital Ventures, and more, with JD Sherman, former President and COO of Hubspot, among its board members. As an AI-native company, we are redefining how businesses drive pipeline and revenue.

Responsibilities

• Design, build, evaluate, deploy, and iterate on scalable Machine Learning systems.
• Drive end-to-end ML initiatives, including problem definition, data exploration, modeling, productionization, and monitoring.
• Understand and continuously improve the Machine Learning stack at Apollo.
• Lead the development of intelligent features powered by LLMs, embeddings, ranking models, and semantic search.
• Guide platform architecture decisions and contribute to foundational ML infrastructure (e.g., feature stores, MLOps).
• Work cross-functionally to define AI-first product experiences and rapidly iterate toward user impact.
• Mentor and uplevel engineers across the organization, influencing engineering best practices and technical direction.
• Champion the use of AI internally to drive engineering and operational efficiency.

Required Qualifications

• 8+ years of experience building and scaling machine learning systems in production environments.
• Strong experience with LLMs and embeddings (e.g., fine-tuning, prompt engineering, vector databases).
• Hands-on experience with Python and modern ML libraries such as PyTorch, TensorFlow, HuggingFace, or Scikit-learn.
• Experience with cloud infrastructure (e.g., GCP), orchestration (Airflow), and experimentation platforms (e.g., mlflow, Databricks).
• Excellent collaboration and communication skills, with the ability to influence across product and engineering teams.
• Proven impact shipping ML-driven features in B2B SaaS products or enterprise platforms.

Preferred Qualifications

• Bachelors, Masters, or a PhD in Computer Science, Mathematics, Statistics, or other quantitative fields, or related work experience.
• Experience with retrieval-augmented generation (RAG), search infrastructure, or related technologies.

Employment Type

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Location Type

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Salary

• [Salary not specified]