PitchBook is looking to build AI & ML solutions and services to solve end-user problems such as summarization, semantic search, and prediction using their extensive data. The goal is to drive unique value for customers through improved data speed, quantity, quality, and discoverability in the PitchBook Platform using AI technologies.
Requirements
- Strong expertise in NLP and machine learning, with hands-on experience in classifiers, large language models (LLMs), and other NLP techniques
- Proven track record of shipping production-grade GenAI and Large Language Model (LLM) systems or services at scale, with measurable impact on product delivery or user experience
- Extensive experience with data pipeline and messaging technologies such as Apache Kafka, Airflow, and cloud data platforms (e.g., Snowflake)
- Expert-level proficiency in Python, SQL, and other relevant programming languages and tools
- Strong understanding of cloud-native technologies and containerization (e.g., Kubernetes, Docker) with experience in managing these systems globally
- Demonstrated ability to solve complex technical challenges and deliver scalable solutions
- 6+ years of experience in software engineering, with a focus on AI & ML technologies, particularly in insights generation, summarization, semantic search, and prediction
Responsibilities
- Lead a multidisciplinary team of engineers and data scientists responsible for building AI & ML solutions and services
- Focus on building scalable and reliable systems that serve as the foundation for PitchBook Platform features
- Provide strong technical direction, problem-solve complex technical challenges, and ensure that the team consistently delivers high-quality, scalable solutions
- Leverage deep knowledge in areas such as advanced natural language processing (NLP), generative AI (GenAI) and large language models (LLMs), ML Operations (MLOps), data architecture, and cloud-managed services
- Oversee the end-to-end lifecycle of AI/ML data systems—from research and development to deployment and operationalization
- Provide hands-on technical leadership in the engineering of AI/ML models and services, focusing on NLP, summarization, semantic search, prediction, classification, and other use cases
- Contribute to the development and application of NLP techniques, including classifiers, transformers, LLMs, and other methodologies, to efficiently leverage structured and unstructured data for insights generation
Other
- Lead, mentor, and develop a high-performing team of engineers and data scientists, fostering a culture of innovation and continuous improvement
- Ensure effective communication and coordination within your team and across geographically dispersed teams
- Work closely with other AI/ML teams, data collection engineering teams, product management, and others to ensure data collection efforts support broader AI/ML goals and product objectives
- Play an active role in recruiting, training, and retaining top engineering talent
- Collaborate with cross-departmental stakeholders, provide leadership across locations, set high standards for the team, and hire, train, and retain exceptional talent
