AiPrise enables fintech and crypto companies to onboard users compliantly and detect and remove fraudsters intelligently. We connect with multiple data sources like Government ID checks, credit bureaus, social media checks, IP address checks, phone number checks and give a simple YES/NO answer about a user to our customers.

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

Must-Have:

• 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.

Nice-to-Have:

• 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.

Success in This Role Looks Like

• 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%+.

Why AiPrise

• 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.

We use a Typescript React frontend coupled with Flask backend hosted on AWS. We also provide our customers with embeddable web SDKs that they can integrate within a day.