Machine Learning Engineer
About The Position
As a Machine Learning Engineer at WireScreen, you will be working across our data systems to unlock the source of truth behind one of the world’s economic powerhouses: China. This role is critical to building models that support the two fundamental pieces of our business: entity resolution and our knowledge graph. These systems are the cornerstones that uncover hidden connections within the Chinese economy. You will be contributing to our existing MCP servers and agentic pipelines to classify, cluster and enrich across millions of entities. You will be working with engineering, product and research to expand our AI toolkit, scaling our data ingestion processes, building analytics and insights into our platform at a scale not previously achievable. Reporting directly to the VP of Engineering, you will work with our data team, enrichment team and product to establish our source of truth and expand our machine learning capabilities.
Requirements
- 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 Haves
- 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
Responsibilities
- 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
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
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
