At PitchBook, the business problem is to innovate, evolve, and invest in AI & ML solutions and services to solve end-user problems, such as summarization, semantic search, and prediction, using PitchBook's industry-leading private, public, and credit markets data.
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
- Experience working in fast-paced environments, particularly in industries that rely on data-intensive technologies (experience in fintech is highly desirable)
Responsibilities
- AI & ML Insights Leadership: Drive the execution of AI & ML initiatives related to PitchBook Platform insights, ensuring that the team's efforts are aligned with overall business goals and strategies
- Technical Oversight: 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.
- Team Leadership & Development: Lead, mentor, and develop a high-performing team of engineers and data scientists, fostering a culture of innovation and continuous improvement.
- GenAI Technologies: 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.
- Cross-functional Collaboration: 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
- Innovation & Continuous Improvement: Continuously explore and implement new technologies and methodologies to enhance the efficiency and accuracy of AI/ML insights generation.
- System Integrity & Security: Ensure that all data collection systems meet the highest standards of integrity, security, and compliance.
Other
- Bachelor's, Master's, or PhD in Computer Science, Mathematics, Data Science, or a related field
- 6+ years of experience in software engineering, with a focus on AI & ML technologies, particularly in insights generation, summarization, semantic search, and prediction
- 3+ years of experience in a leadership role as a technical lead or engineering manager
- Excellent communication skills with a collaborative approach to working with global teams and stakeholders
- Ability to work in a standard office setting, with limited corporate travel required
