HarbourVest Partners
Quantitative Developer
Boston
Sponsorship not specified$140k-$155kDetected 30 days ago
PythonSQLVector DatabasesCloud PlatformsCI/CDMachine LearningData EngineeringLLMsRAGAgentic AIMLOpsAI OrchestrationStatisticsResearchCollaboration
About the role
- Job Description Summary Seated within our Quantitative Investment Science group, this position turns machine learning, applied AI, and agentic workflow capabilities into reliable investment workflow software.
- Our total rewards offerings are influenced by several business factors, and eligibility for certain components will vary by position and geography.
Responsibilities
- Build and productionize ML models, feature pipelines, and inference workflows for QIS applications
- Develop semantic matching, ranking, recommendation, and peer-selection systems for funds, managers, deals, companies, and comparable opportunities
- Build unstructured data intelligence, classification, enrichment, and AI-assisted review workflows for complex internal materials and operational datasets
- Design agentic AI workflows that can plan multi-step analyses, call internal tools, retrieve relevant context, and produce traceable recommendations for human review
- Create evaluation frameworks for AI agents, including task success metrics, regression suites, prompt/version tracking, guardrail tests, and failure-mode analysis
- Create model evaluation harnesses, benchmark datasets, backtests, monitoring, drift detection, and quality gates so ML outputs can be measured and trusted
- Partner with data and platform engineers to make ML workflows repeatable, observable, secure, and easy to operate
- Establish practical MLOps patterns for experiment tracking, model versioning, deployment, rollback, audit trails, and production support
Requirements
- Strong proficiency in Python and modern software engineering practices
- Ability to learn and apply the right ML, statistical, and data engineering tools for the problem, with sound judgment around model choice, data representation, reproducibility, and production constraints
- Practical experience with embeddings, semantic search, ranking, recommendation systems, information extraction, agentic AI systems, or LLM-enabled workflows
- Familiarity with agent patterns such as tool use, retrieval-augmented generation, planning, memory, workflow orchestration, and structured human review
- Strong testing habits and ability to debug model behavior using real data, logs, metrics, and user feedback
- Familiarity with cloud platforms, containerized development, CI/CD, observability, and secure production deployment patterns
- Experience with applied machine learning, including feature engineering, model training, evaluation, inference, and monitoring
- Strong SQL skills and comfort designing data models for analytical or product-facing systems
- Experience building production services, APIs, batch jobs, queues, or scheduled pipelines around data-intensive workflows
- Ability to explain model behavior, data limitations, quality tradeoffs, and operational risk to technical and non-technical partners
Nice to have
- Healthy skepticism about model outputs, with strong instincts for evaluation, backtesting, monitoring, and human review
- Comfort turning ambiguous analytical workflows into measurable, maintainable production systems
- Strong collaboration skills across quant developers, data engineering, product, and investment stakeholders
- Curiosity about finance, private markets, and the data problems behind investment decision-making
- experience with financial data, time series data, private markets workflows, vector databases, agent frameworks, unstructured data processing, feature stores, model registries, or multi-tenant enterprise systems
Compensation
- $140,000.00 - $155,000.00
- This USD base salary range represents only one component of total compensation for this role and is provided in accordance with local requirements.
- This role is eligible for a discretionary annual bonus, which is determined based on individual and overall firm performance.
- In addition to salary and bonus, total compensation may include eligibility for long-term reward programs and a comprehensive total rewards package that may include retirement, health, insurance, paid time off, and wellness programs.
- Please note the posted ranges do not apply outside the U.S. and should not be converted to other currencies as a proxy for compensation in other countries.
Benefits
- Education Preferred
- Bachelor of Science (B.S.) or Master's in Computer Science, Machine Learning, Statistics, Mathematics, Engineering, or equivalent experience
Apply directly at HarbourVest Partners →Create a free account for alerts like thisView HarbourVest Partners immigration profile
This listing is sourced directly from HarbourVest Partners's careers page and normalized into a canonical job model.