Machine Learning Engineer

Responsibilities

• Refine our existing entity resolution algorithms to reveal hidden connections between people and organizations across China
• Expand the knowledge graph by incorporating alternative data to map the power structure of China
• Train, validate, and deploy ML models that operate on tens of millions of records daily
• Partner with Product to design and implement evaluation harnesses for classical ML and agentic systems
• Integrate agent workflows into internal tools to enhance the scale and speed of the Research team

Requirements

• 4+ years of experience tackling clustering-type ML problems, ideally in the domain of knowledge graphs or entity resolution; other domains may include recommendation engines, cohort analysis, or outlier/anomaly detection
• End-to-end machine learning model experience in production, including experimentation, training, testing, tuning, deployment, and ongoing operation; model families may include clustering, classification/regression, dimensionality reduction and embeddings, nearest-neighbor/similarity methods (e.g. KNN, SVM), ensembles, NLP, and deep learning
• Significant experience with Python programming and SQL

Technologies

• Python
• SQL
• PySpark
• Temporal
• FastAPI
• Scikit-learn
• NumPy
• Docker
• Terraform
• Kubernetes

Benefits

• Competitive compensation including salary, equity, and rapid growth potential
• 100% company-paid Medical, Dental, and Vision coverage for employees
• FSA, HSA, and 401(k) options to help you plan for healthcare expenses and retirement
• Generous paid time off plus company-wide holidays to help you rest and recharge
• Pre-tax commuter benefits to help you save on transit and parking
• Hybrid office schedule designed to give you flexibility while staying connected with your team

Nice to Have

• Experience working with frontier or state-of-the-art models and/or fine-tuning your own LLMs for specific tasks
• Experience solving problems across large, heterogeneous unstructured datasets and/or with semantic search, computer vision (OCR), or linear optimization problems
• Experience with any of the following technologies: PySpark, Temporal, FastAPI, Scikit-learn, NumPy, Docker, Terraform, Kubernetes
• Early-stage startup experience (Series B or earlier)
• B2B SaaS experience
• #LI-LG1