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Engineering Manager, Machine Learning OperationsNew York, New York, United States

Engineering Manager, Machine Learning OperationsNew York, New York, United States

PitchBook DataNew York, NY, US
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Engineering Manager, Machine Learning Operations

At PitchBook, we are always looking forward. We continue to innovate, evolve, and invest in ourselves to bring out the best in everyone. We're deeply collaborative and thrive on the excitement, energy, and fun that reverberates throughout the company.

Our extensive learning programs and mentorship opportunities help us create a culture of curiosity that pushes us to always find new solutions and better ways of doing things. The combination of a rapidly evolving industry and our high ambitions means there's going to be some ambiguity along the way, but we excel when we challenge ourselves. We're willing to take risks, fail fast, and do it all over again in the pursuit of excellence.

If you have a good attitude and are willing to roll up your sleeves to get things done, PitchBook is the place for you.

About the Role

As a member of the Product and Engineering team at PitchBook, you will be part of a team of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and the drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation.

We know that greatness is achieved through collaboration and diverse points of view, so we work closely with partners around the globe. As a team, we assume positive intent in each other's words and actions, value constructive discussions, and foster a respectful working environment built on integrity, growth, and business value. We invest heavily in our people, who are eager to learn and constantly improve. Join our team and grow with us!

As an Engineering Manager, Machine Learning (ML) Operations in the Technology & Engineering division, you will be responsible for leading and managing PitchBook's MLOps team. The team is responsible for enabling PitchBook'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.

Primary Job Responsibilities

  • 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 PitchBook, 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 PitchBook'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

Skills and Qualifications

  • Bachelor's, Master's, or PhD in Computer Science, Mathematics, Data Science, or a related field
  • 5+ 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% : PyTorch, Tensorflow, LangChain, scikit-learn, Redis, Elasticsearch, Amazon SageMaker, Google Vertex AI, Weights & Biases, FastAPI, Prometheus, Grafana, Apache Kafka, Apache Airflow, MLflow, and KubeFlow
  • 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 GitOps and creation / management of CI / CD pipelines
  • Demonstrated experience building and using SQL / NoSQL 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
  • Benefits + Compensation at PitchBook

    Physical Health

  • Comprehensive health benefits
  • Additional medical wellness incentives
  • STD, LTD, AD&D, and life insurance
  • Emotional Health

  • Paid sabbatical program after four years
  • Paid family and paternity leave
  • Annual educational stipend
  • Ability to apply for tuition reimbursement
  • CFA exam stipend
  • Robust training programs on industry and soft skills
  • Employee assistance program
  • Generous allotment of vacation days, sick days, and volunteer days
  • Social Health

  • Matching gifts program
  • Employee resource groups
  • Subsidized emergency childcare
  • Dependent Care FSA
  • Company-wide events
  • Employee referral bonus program
  • Quarterly team building events
  • Financial Health

  • 401k match
  • Shared ownership employee stock program
  • Monthly transportation stipend
  • Please be aware the above PitchBook benefit and perk offerings are subject to corresponding plan and policy documents and may change during the course of your employment.
  • Compensation

  • Annual base salary : $240,000-$280,000
  • Target annual bonus percentage : 15%
  • Starting pay will be based on several factors and commensurate with qualifications & experience. We also have a location-based compensation structure; there may be different ranges for candidates by location.
  • Working Conditions

    We believe our business and our culture are strongest when we work together in person. We also know that it's helpful to have some flexibility to work remotely. Most roles work in the office 3+ days / week, and some are expected to work in the office 4-5 days / week. The current expectation for this role is that you are working in the office 4+ days / week and that you are in the office full-time during the training period, for which the length varies by role. During an initial phone screen, the team will discuss expectations for this specific position.

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    Engineering Manager • New York, NY, US

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