Machine Learning Engineer

• 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
• 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 salary, equity, and role trajectory: Experience rewarding work and rapid growth potential within a swiftly scaling company
• FSA, HSA, & 401(k): Save for retirement and healthcare expenses with 401(k), HSA, and FSA options.
• Paid time off: Take time off to rest and rejuvenate. We offer company-wide paid holidays as well as flexible vacation time.
• Medical, dental, and vision: We offer medical, dental, and vision insurance for employees and dependents.
• Flexible in-person culture: Our hybrid roles allow flexibility to work from home while also enjoying in-person collaboration.

• 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
• 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
• Early-stage startup experience (Series B or earlier)
• Experience with any of the following technologies: PySpark, Temporal, FastAPI, Scikit-learn, NumPy, Docker, Terraform, Kubernetes
• B2B SaaS experience