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This range is provided by AiPrise. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range
$75,000.00/yr - $150,000.00/yr
About AiPrise
AiPrise is a global compliance orchestration platform helping fintechs, marketplaces, and payment companies verify and onboard customers worldwide. We integrate with 80+ identity and compliance vendors to deliver a holistic view of risk. We’re now building AI-powered compliance agents to revolutionize KYB, AML, sanctions screening, and risk scoring — enabling our customers to onboard faster, reduce manual reviews, and prevent financial crime.
Role Overview
We’re looking for a Machine Learning Engineer to lead the development of our AI compliance agent from prototype to production. This role will own the design, development, and deployment of ML/NLP systems for KYB verification, sanctions/PEP screening, adverse media analysis, and merchant risk scoring , tightly integrated with our case management and orchestration platform.
You will work closely with our compliance, product, and engineering teams to ship a high-accuracy AI agent in 3 months and scale it globally in 9 months .
What You’ll Do
- Design & Build Core AI Modules
- Develop NLP pipelines for adverse media monitoring and summarization across multiple languages.
- Implement entity resolution models to auto-clear false positives in sanctions/PEP checks.
- Build AI-driven document understanding for KYB documents (e.g., corporate registrations, licenses).
- Create a unified risk scoring model combining KYB, AML, and contextual data.
- Deploy & Scale
- Architect models for low-latency, high-throughput processing at scale.
- Monitor production performance, ensuring accuracy, speed, and cost-efficiency.
- Continuously retrain and refine models based on feedback and evolving risk patterns.
What We’re Looking For
- 6+ years of experience in ML engineering or applied data science, with a focus on NLP or compliance/fraud/risk systems.
- Strong proficiency in Python, PyTorch or TensorFlow, and modern NLP libraries (e.g., Hugging Face Transformers, spaCy).
- Experience building named entity recognition (NER), entity resolution, and text classification systems.
- Familiarity with LLMs and prompt engineering for compliance/risk use cases.
- Experience deploying ML models to production (preferably in AWS/GCP).
- Strong understanding of data pipelines, APIs, and microservices.
- Proven ability to translate business requirements into technical ML solutions.
- Experience in RegTech, FinTech, AML, KYC/KYB, or fraud detection.
- Knowledge of vector databases (Pinecone, Weaviate, etc.) for semantic search.
- Familiarity with multi-language NLP for global coverage.
- Experience with graph databases for UBO mapping and relationship risk analysis.
- In 3 Months: A production-ready AI agent for onboarding compliance that’s integrated with our case management, delivering explainable KYB, sanctions, and adverse media insights to analysts.
- In 9 Months: A fully scaled AI compliance agent handling risk scoring, ongoing monitoring, and merchant risk analysis for multiple enterprise customers, reducing manual reviews by 70%+.
- Build mission-critical AI that directly fights financial crime and fraud globally.
- Work with massive, diverse datasets from 200+ countries.
- Join a fast-moving YC-backed startup with global customers like Meta and leading fintechs.
- Ship quickly — your models will be in production in weeks, not years.
Seniority level
Seniority level
Mid-Senior level
Employment type
Employment type
Full-time
Job function
Job function
Engineering and Information Technology
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