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. Apollo.io provides sales and marketing teams with easy access to verified contact data for over 270 million B2B contacts, 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. Apollo.io is growing rapidly, with 900% revenue growth since 2021, and is looking for world-class talent to keep building with us.
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
- 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 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.
What You’ll Love About Apollo
Besides the great compensation package and culture that thrives in openness and excellence, we invest tremendous effort into developing our remote employees’ careers. The team embraces that we have a sole purpose: to help customers maximize their full revenue potential on the Apollo platform. This mindset opens us up to a lot of creative approaches to making customers successful at scale. You’ll be a significant part of a lean, remote team, empowered to really own your role as a proactive educator. We’re very collaborative at Apollo, so you’ll be able to lean on your teammates, even in adjacent departments, to help you achieve lofty goals. You’ll be supported and encouraged to experiment and take educated risks that lead to big wins. And, you’ll have a whole team remotely by your side to help you do it!
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