Machine Learning Engineer
Job Description
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.
As a Machine Learning Engineer, you will lead the development of our AI compliance agent from prototype to production. This role involves designing, developing, and deploying 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'll 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. Success in this role means delivering a production-ready AI agent for onboarding compliance that's integrated with our case management system, providing explainable KYB, sanctions, and adverse media insights to analysts.
Key Technical Aspects:
- Building NLP pipelines for multi-language adverse media monitoring
- Implementing entity resolution models for sanctions/PEP checks
- Developing AI-driven document understanding systems
- Creating unified risk scoring models
- Architecting for scale and performance
Why Join AiPrise:
- Work on mission-critical AI fighting financial crime globally
- Access to massive, diverse datasets from 200+ countries
- Join a fast-moving YC-backed startup with enterprise customers
- Rapid deployment of models to production
The role offers an opportunity to make a significant impact in the fintech compliance space while working with cutting-edge AI technologies. You'll be at the forefront of developing solutions that help prevent financial crime and make the financial system safer and more efficient.
Responsibilities For Machine Learning Engineer
- Lead development of AI compliance agent from prototype to production
- Design and develop ML/NLP systems for KYB verification, sanctions screening, and risk scoring
- Develop NLP pipelines for adverse media monitoring across multiple languages
- Implement entity resolution models to auto-clear false positives in sanctions/PEP checks
- Build AI-driven document understanding for KYB documents
- Create a unified risk scoring model combining KYB, AML, and contextual data
- Architect models for low-latency, high-throughput processing at scale
- Monitor production performance, ensuring accuracy, speed, and cost-efficiency
Requirements For Machine Learning Engineer
- 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
- 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
Benefits For Machine Learning Engineer
- Ship quickly — your models will be in production in weeks, not years
