AI/ML Engineering Manager

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, 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.

Engineering Manager, Machine Learning 

Your Role & Mission

As the Engineering Manager of our Machine Learning team, you will have the critical leadership role of enabling excellence, productivity, and growth within Apollo's engineering organization. You will be leading the development of our Machine Learning products by working in close collaboration with your cross-functional partners. You crave the opportunity for hands-on mentorship, and to accelerate not only your career, but for those of your team as well. Your responsibility would come in several forms, including but not limited to:

• Help the Machine Learning team define, set, and adhere to goals and expectations
• Drive a culture around excellence, learning, and fun
• Critically observe and improve development and management processes within Apollo engineering
• Work closely with key stakeholders such as the CTO, Product Managers, and Designers to deliver high quality Machine Learning products (like lead scoring, recommendations, LLM based products, AI agents, etc.) at a rapid pace for an ever-increasing user base
• Change, and be a part of key decision-making processes within the engineering organization

Daily Adventures and Responsibilities

• Participation in key technical decision-making discussions such as sprint planning, software design, and occasionally code reviews
• Help build and scale a world-class engineering team by sourcing and hiring candidates
• Hold systematic weekly 1:1 touch points with engineers to deliver and receive quality feedback
• Work with engineers to develop and execute on personalized goals
• Conduct objective and helpful quarterly performance reviews for engineers

Competencies

• You love scaling up through well-written documents and well-defined processes. As a remote first company, documentation is critical to our hyper-growth and success.
• You are compassionate, put people first as a mentor, and are tactful with both accepting and delivering criticism to others.
• You have the leadership skills to think and execute strategically but are not afraid to get your hands dirty when needed.
• Your technical understanding of engineering systems, especially related to data and machine learning, is second to none.
• You can relate to and admire Apollo’s values of Extreme Ownership, Customer Obsession, Be All for One, Learn Voraciously, Speak and Act Courageously, and Move with Focus & Urgency.

Skills and Relevant Experiences

• 3-5 years' experience in people management, preferably leading senior engineers and staff engineers
• 8+ years of experience building Machine Learning or AI systems 
• Experience deploying and managing machine learning models in the cloud 
• 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: 
• Experience with Databricks, Google Cloud Platform, Snowflake, mlflow, and Airflow 
• Experience with Large Language Models (LLMs) or similar technologies 
• Experience with one or more of the following: natural language processing, deep learning, recommendation systems, search relevance & ranking, and speech-to-text conversion.

Great to have

• PhD in Computer Science or related field with a focus on machine learning