WireScreen

Machine Learning Engineer

Reposted 20 Days Ago

New York, NY, USA

Hybrid

150K-195K Annually

Mid level

Big Data • Software • Business Intelligence

The most trusted intelligence on companies in China

The Role

Build and deploy ML models and pipelines for entity resolution and a knowledge graph at scale. Fine-tune algorithms, expand data ingestion and enrichment, create evaluation harnesses, and integrate agentic workflows to support research and product teams processing tens of millions of records daily.

Summary Generated by Built In

WireScreen is a fast-growing Series A startup bringing clarity to one of the world’s most complex business landscapes. We’re building the go-to intelligence platform for navigating global supply chains and China-related risk—revealing the networks, relationships, and financial ties behind companies so our customers can see connections, remove obstacles, and make confident decisions.

Backed by Sequoia Capital and Harpoon Ventures, our team includes a two-time Pulitzer Prize–winning journalist and senior engineers from Google, Twitter, and Oracle. We launched just three years ago and already have strong traction with top-tier government customers—and we’re just getting started. If you’re excited to make global systems more transparent and secure, now’s the perfect time to join us.

About The Role:

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.

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
#LI-LG1

What You'll Love About Wirescreen

At WireScreen, you'll do high-impact work that helps shape the global economy and power competition. We’re a mission-driven team with a growth mindset—curious, collaborative, and unafraid to take on bold challenges. You’ll be empowered to act, heard when you speak, and supported as you grow. With strong market momentum and ambitious goals, this is an exciting time to join us and help build something that truly matters.

Benefits & Perks

At WireScreen, we care deeply about our team and are committed to supporting your well-being—both in and out of the workplace. Here’s how we take care of our employees:

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

Skills Required

4+ years of experience working on clustering-type ML problems (entity resolution, recommendation, cohort analysis, anomaly detection)
End-to-end production ML experience: experimentation, training, testing, tuning, deployment, and monitoring
Significant experience with Python programming and SQL
Experience fine-tuning or working with frontier / SOTA models and LLMs
Experience with large, heterogeneous, messy unstructured datasets, semantic search, computer vision (especially OCR), or linear optimization
Experience with PySpark, Temporal, FastAPI, Scikit-learn, NumPy, Docker, Terraform, Kubernetes
Early-stage startup experience (Series B or earlier)
B2B SaaS experience

WireScreen Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about WireScreen and has not been reviewed or approved by WireScreen.

Healthcare Strength — Healthcare coverage includes medical, dental, and vision for employees (and dependents), with HSA/FSA options; some postings indicate employee premiums are fully company-paid. This scope signals comprehensive health support for a company of this size and stage.
Leave & Time Off Breadth — Time off includes flexible PTO, paid holidays, and paid sick days, with policies described as generous. Flexibility in time away is emphasized alongside a hybrid work model.
Wellbeing & Lifestyle Benefits — Work setup features hybrid flexibility, commuter benefits, and office perks such as company-sponsored outings, happy hours, and snacks. These elements indicate attention to day-to-day wellbeing beyond base pay.