Senior Machine Learning Engineer II
Apollo.io is the leading go-to-market solution for revenue teams, trusted by over 500,000 companies and millions of users globally, from rapidly growing startups to some of the world's largest enterprises. Founded in 2015, the company is one of the fastest growing companies in SaaS, raising approximately $250 million to date and valued at $1.6 billion. Apollo.io provides 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. By helping revenue professionals find the most accurate contact information and automating the outreach process, Apollo.io turns prospects into customers. Apollo raised a series D in 2023 and is backed by top-tier investors, including Sequoia Capital, Bain Capital Ventures, and more, and counts the former President and COO of Hubspot, JD Sherman, among its board members.Working at Apollo:
We are a remote-first inclusive organization focused on operational excellence. Our way of working ensures clear expectations and an environment to do your best work with ample reward.
Your Role & Mission:
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 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, self-healing (restartable/graceful failures) features while productionizing data & ML workflows
Write unit/integration tests and contribute to engineering wiki
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 great attention to detail
Acts with the utmost integrity
Genuinely curious and open; loves learning
Critical thinking and proven problem-solving skills required
Required Qualifications:
Bachelors, Masters, or a PhD in Computer Science, Mathematics, Statistics, or other quantitative fields or related work experience
8+ 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 production environment, primarily using Python
Experience with Machine Learning software tools and libraries (e.g., Scikit-learn, TensorFlow, Keras, PyTorch, etc.)
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.
Why You’ll Love Working at Apollo
At Apollo, we’re driven by a shared mission: to help our customers unlock their full revenue potential. That’s why we take extreme ownership of our work, move with focus and urgency, and learn voraciously to stay ahead.
We invest deeply in your growth, ensuring you have the resources, support, and autonomy to own your role and make a real impact. Collaboration is at our core—we’re all for one, meaning you’ll have a team across departments ready to help you succeed. We encourage bold ideas and courageous action, giving you the freedom to experiment, take smart risks, and drive big wins.
If you’re looking for a place where your work matters, where you can push boundaries, and where your career can thrive—Apollo is the place for you.
Apply Now
We are a remote-first inclusive organization focused on operational excellence. Our way of working ensures clear expectations and an environment to do your best work with ample reward.
Your Role & Mission:
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 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, self-healing (restartable/graceful failures) features while productionizing data & ML workflows
Write unit/integration tests and contribute to engineering wiki
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 great attention to detail
Acts with the utmost integrity
Genuinely curious and open; loves learning
Critical thinking and proven problem-solving skills required
Required Qualifications:
Bachelors, Masters, or a PhD in Computer Science, Mathematics, Statistics, or other quantitative fields or related work experience
8+ 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 production environment, primarily using Python
Experience with Machine Learning software tools and libraries (e.g., Scikit-learn, TensorFlow, Keras, PyTorch, etc.)
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.
Why You’ll Love Working at Apollo
At Apollo, we’re driven by a shared mission: to help our customers unlock their full revenue potential. That’s why we take extreme ownership of our work, move with focus and urgency, and learn voraciously to stay ahead.
We invest deeply in your growth, ensuring you have the resources, support, and autonomy to own your role and make a real impact. Collaboration is at our core—we’re all for one, meaning you’ll have a team across departments ready to help you succeed. We encourage bold ideas and courageous action, giving you the freedom to experiment, take smart risks, and drive big wins.
If you’re looking for a place where your work matters, where you can push boundaries, and where your career can thrive—Apollo is the place for you.
Apply Now