Engineering Manager, Machine Learning Operations

About the Role

As an Engineering Manager, Machine Learning (ML) Operations in the Technology & Engineering division, you will be responsible for leading and managing Pitch Book’s MLOps team. The team is responsible for enabling Pitch Book’s Machine Learning teams and practitioners by providing tools and golden paths that optimize all aspects of the Machine Learning Development Life Cycle (MLDLC). Your team’s work will support projects in a variety of domains, including Generative AI (GenAI), Large Language Models (LLMs), Natural Language Processing (NLP), Classification, and Regression.

Your role will be critical in driving AI (Artificial Intelligence) innovations across the organization.

• Lead the MLOps team direction and execution (operations, processes, practices, and standards), working closely with engineering leadership and product management to craft roadmaps, define KPIs, and achieve success criteria.
• Ensure effective communication and coordination across geographically dispersed teams. Oversee the enablement of scalable solutions that meet high standards of reliability and efficiency.
• Champion the adoption and integration of ML best practices at Pitch Book, fostering a culture of innovation and experimentation to drive the development of high-quality AI products.
• Serve as a force multiplier by removing roadblocks, implementing process improvements, providing frequent and actionable feedback to team members, and building practices for ideation and innovation.
• Bridge the gap between business/product needs and execution, including building and delivering on group-level objectives and key results, identifying resource needs, and building execution plans for initiatives.
• Ensure MLOps roadmap items are delivered on time and have exceptional quality.
• Learn constantly and be passionate about discovering new tools, technologies, libraries, and frameworks (commercial and open source), that can be leveraged to improve Pitch Book’s AI capabilities.
• Describe technical content in intuitive ways for a variety of audiences, adapting communication from highly technical deep dives with engineers to non-technical dialogue with executive stakeholders.
• Establish and drive a culture founded on creating belonging, psychological safety, candor, connection, cooperation, and fun.
• Understand how to apply agile, lean, and principles of fast flow to team efficiency and productivity.
• Support the vision and values of the company through role modeling and encouraging desired behaviors.
• Participate in various company initiatives and projects as requested.

• Bachelor’s, Master’s, or PhD in Computer Science, Mathematics, Data Science, or a related field.
• 3+ years of experience in an engineering leadership role, managing globally distributed teams.
• 6+ years of experience in hands-on development of Machine Learning algorithms
  .
• 6+ years of experience in hands-on deployment of Machine Learning services
  .
• 6+ years of experience supporting the entire MLDLC
  , including post-deployment operations such as monitoring and maintenance
  .
• 6+ years of experience with Amazon Web Services (AWS) and/or Google Cloud Platform (GCP).
• Experience with at least 70% of:
  Py Torch ,
  Tensorflow
  , Lang Chain
  , scikit-learn
  , Redis
  , Elasticsearch
  , Amazon Sage Maker
  , Google Vertex AI
  , Weights & Biases
  , FastAPI
  , Prometheus
  , Grafana
  , Apache Kafka
  , Apache Airflow
  , MLflow
  , and Kube Flow
  .
• Ability to break large, complex problems into well-defined steps, ensuring iterative development and continuous improvement.
• Experience in cloud-native delivery with a deep practical understanding of containerization technologies such as Kubernetes and Docker
  , and the ability to manage these across different regions.
• Proficiency in Git Ops and creation/management of CI/CD pipelines
  .
• Demonstrated experience building and using SQL/No
  
  SQL databases
  .
• Demonstrated experience with Python (Java is a plus) and other relevant programming languages and tools.
• Excellent problem-solving skills with a focus on innovation, efficiency, and scalability in a global context.
• Strong communication and collaboration skills, with the ability to engage effectively with internal customers across various cultures and regions.
• Ability to be a team player who can also work independently.
• Experience working across multiple development teams is a plus.
• Proficiency with the Microsoft Office suite including in-depth knowledge of Outlook
  , Word
  , and Excel with the ability to pick up new systems and software easily.
• Must be authorized to work in the United States without the need for visa sponsorship now or in the future.