Senior Machine Learning Engineer

Key Skills

Aartificial intelligence, Apache Airflow, Databricks, Deep Learning, Effective communication skills, Keras software library, Large Language Models - LLMs, Machine learning techniques, MLflow, Natural Language Processing (NLP), Python Programming, PyTorch, Scikit-learn, Snowflake, TensorFlow

Job Description

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.