Machine Learning Engineer
About The Position
As a Machine Learning Engineer on PitchBook’s AI & ML (Insights) team, you will develop AI-powered features that extract insights from structured and unstructured data, including reports and news. The role involves designing, building, training, deploying, and maintaining machine-learning models and services that power user-facing features on the PitchBook Platform. Your focus will include NLP, generative AI, large language models, and scalable data systems, with work spanning model architecture and operationalization. You will address complex technical challenges, contribute to architectural decisions, and collaborate with engineers, data scientists, product managers, and data collection teams. Your work will help improve the speed, discoverability, quality, and quantity of customer insights by inferring meaning and structure from millions of data sources and enriching datasets with predictive and generative intelligence. The position is expected to be in the office five days a week in a standard office setting. Employees use a PC and phone throughout the day. Limited corporate travel to remote offices or other business meetings and events may be required.
Requirements
- Bachelor’s degree in Computer Science, Mathematics, or Data Science.
- At least 2 years of experience in software engineering or machine-learning engineering, focused on AI/ML applications in insight generation, summarization, semantic search, and prediction.
- Authorization to work in the United States without visa sponsorship now or in the future.
Nice To Haves
- Hands-on expertise in NLP and machine learning, including classifiers, transformer models, LLMs, and libraries such as scikit-learn, pandas, NumPy, TensorFlow, and PyTorch.
- Experience delivering production-grade GenAI or LLM-based systems with measurable business impact.
- Familiarity with the LangChain ecosystem, including LangSmith and LangGraph, and experience using them in production.
- Experience building and maintaining scalable data pipelines and distributed systems using technologies such as Apache Kafka, Airflow, and cloud data platforms such as Snowflake.
- Strong Python and SQL skills; Java or Scala knowledge is a plus.
- Practical experience with cloud-native development, containerization, and orchestration technologies such as Docker and Kubernetes.
- Ability to solve complex technical problems, contribute to architectural decisions, and deliver high-performance, reliable solutions.
- Excellent communication and collaboration skills, including cross-functional work with product managers, engineers, and data scientists in globally distributed teams.
- Experience in fast-paced, data-driven environments; fintech or financial data platform exposure is an advantage.
- Research papers published at peer-reviewed AI/ML conferences such as NeurIPS, ICML, or ACL, and participation in the broader AI research community.
Responsibilities
- Deliver high-impact AI and machine-learning capabilities that drive insight generation on the PitchBook Platform and align with business goals and team priorities.
- Design, build, and deploy AI/ML models and services, particularly for NLP, summarization, semantic search, classification, and prediction.
- Contribute to scalable, high-performance systems that meet production reliability and efficiency standards.
- Build and optimize models using classifiers, transformers, LLMs, and other NLP techniques to generate insights from structured and unstructured data.
- Integrate models into the broader AI/ML infrastructure with partner teams.
- Collaborate with engineering, product management, and data collection teams to ensure models use high-quality data and support product goals.
- Explore emerging GenAI, NLP, and search technologies, and translate research into practical solutions.
- Contribute to model transparency, monitoring, evaluation, and compliance, while maintaining security, data integrity, and responsible AI standards.
- Share knowledge, pair with teammates, participate in code and design reviews, provide situational guidance to junior engineers, and contribute to team best practices.
- Participate in candidate technical evaluation and help onboard team members through documentation, pairing, and knowledge sharing.
- Apply Agile, Lean, and Fast-Flow principles to support efficient model development and deployment.
- Support company initiatives and model the company’s vision and values.
Benefits
- Comprehensive health benefits and additional medical wellness incentives.
- Short-term disability, long-term disability, AD&D, and life insurance.
- Paid sabbatical program after four years.
- Paid family and paternity leave.
- Annual educational stipend.
- Tuition reimbursement eligibility.
- CFA exam stipend.
- Training programs on industry and soft skills.
- Employee assistance program.
- Vacation, sick, and volunteer days.
- Matching gifts program.
- Employee resource groups.
- Subsidized emergency childcare.
- Dependent Care FSA.
- Company-wide events and quarterly team-building events.
- Employee referral bonus program.
- 401(k) match.
- Shared-ownership employee stock program.
- Monthly transportation stipend.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
