Engineering Manager, PitchBook

Machine Learning Operations

$240-280k

+ Shared ownership employee stock program + Target annual bonus percentage: 15%

SQL

AWS

Docker

Kubernetes

GCP

Python

Java

Kafka

Elasticsearch

Redis

Airflow

Excel

Tensorflow

Scikit-Learn

Prometheus

Kubeflow

Grafana

PyTorch

Sagemaker

FastAPI

Senior and Expert level

New York

More information about location

4-5 days a week in office

Private equity & venture capital database

Open for applications

Private equity & venture capital database

1001+ employees

B2BAnalyticsMarket researchSaaSVenture CapitalCapital Markets

Open for applications

$240-280k

+ Shared ownership employee stock program + Target annual bonus percentage: 15%

SQL

AWS

Docker

Kubernetes

GCP

Python

Java

Kafka

Elasticsearch

Redis

Airflow

Excel

Tensorflow

Scikit-Learn

Prometheus

Kubeflow

Grafana

PyTorch

Sagemaker

FastAPI

Senior and Expert level

New York

More information about location

4-5 days a week in office

1001+ employees

B2BAnalyticsMarket researchSaaSVenture CapitalCapital Markets

Company mission

To provide thousands of global business professionals with comprehensive data on the private and public markets to help them discover and execute opportunities with confidence.

Job

Company

Role

Who you are

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

What the job involves

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.
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
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

Our take

Recognizing the need for actionable and extensive intelligence in the private equity sector, PitchBrook was founded in 2007 with the vision to create a resource for comprehensive data, research, and insights spanning the global capital markets.

To address the complexity of these markets, PitchBook has continually expanded its coverage, integrating thousands of datasets and millions of individual insights into its platform. The company's dedication to innovation is evident in the pioneering features and products introduced to surface critical information for its clients.

PitchBook's integration into Morningstar since 2016 has provided a solid foundation for sustained growth and development. The company's commitment to helping clients make informed decisions suggests a future of ongoing evolution and expansion, as it remains at the forefront of providing indispensable resources for navigating the complexities of the global capital markets.

Kirsty

Company Specialist at Welcome to the Jungle

Insights

Glassdoor (4)

Company

Funding (2 rounds)

Jan 2016

$10m

SERIES B

Sep 2009

$3.8m

SERIES A

Total funding: $13.8m

Company benefits

Additional medical wellness incentives
Paid sabbatical program after four years
Paid parental leave
Annual educational stipend
Robut training programs on industry and soft skills
Employee resource groups
Company-wide events
Employee referral bonus program
Quarterly team building events
Shared ownership employee stock program
Monthly transportation stipend
Comprehensive health benefits
STD, LTD, AD&D and life insurance
Ability to apply for tuition reimbursement
CFA exam stipend
Employee assistance program
Generous allotment of vacation days, sick days and volunteer days
Matching gifts program
Subsidized emergency childcare
Dependent Care FSA
401k match

Company HQ

Central Business District, Seattle, WA

Leadership

John Gabbert

(CEO)

Previously the Managing Director of Private Markets at Dow Jones. Also spent over 6 years at VentureOne in multiple roles, including Director of Reseach/Operations and VP of Worldwide Research.

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