AI Engineer
Build full-stack AI prototypes and agentic systems to pressure-test venture ideas. Requires 3+ years building production AI applications with strong frontend/backend fluency and frontier coding agent expertise.
Machine Learning Engineer
Build and deploy ML models for entity resolution and knowledge graph expansion on large-scale China-related data. Requires 4+ years clustering ML experience and end-to-end production ML with Python/SQL.
150k – 195kNew York, NYML EngineeringHybrid4+ YOE
About the role
What You'll Do
- Fine tune our existing entity resolution algorithms to uncover hidden connections between people and organizations across China
- Expand our knowledge graph with alternative data to map out the power structure of China
- Train, test and deploy ML models that operate on tens of millions of records daily
- Work with Product to define and implement evaluation harnesses for classical ML and agentic systems
- Build agent workflows into internal tools to improve the scale and speed of our Research team
What we’re looking for
- 4+ years of experience working on clustering-type ML problems, ideally in the domain of knowledge graphs / entity resolution, but other domains could include; recommendation engines, cohort analysis, outlier/anomaly detection
- End-to-end machine learning model experience in production; that you’ve stood up a service including experimenting, training, testing and tuning a job against a dataset all the way through to deployment and beyond. Model families could 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
Nice to have
- Experience working with Frontier/SOTA models and/or fine-tuning your own LLMs for specific tasks
- Working on problems across large, heterogeneous, messy unstructured datasets and/or with semantic search, computer vision (especially 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
Skills
PythonSQLMachine LearningEntity ResolutionKnowledge GraphsClusteringNLPscikit-learnNumPyPysparkFastAPIDockerKubernetesTerraformTemporal
Similar roles
ML Engineering jobsResearch Engineer, Post-Training
Research Engineers design and run post-training workflows, build evaluation infrastructure, and turn frontier AI techniques into reliable production systems for enterprise customers. Requires experience with fine-tuning, RLHF, reward modeling, and strong experimentation skills.
Research Engineer, Agents
Research Engineers build and productionize agentic AI systems, designing compound architectures, evaluation frameworks, and reliable execution for enterprise workflows. Requires strong Python skills, systems reasoning, and experience building agents with tools, retrieval, planning, and memory.
ML Engineer
Build and deploy production ML models and pipelines to detect suspicious activity, improve verification accuracy, and support threat intelligence workflows.