Data Scientist I
Core
Implementing generative AI and machine learning solutions for Anti-Money Laundering (AML) transaction monitoring.
Role type
Senior IC machine-learning engineer (generative AI)
Builds
AI-based transaction monitoring systems, content generation systems, and evaluation frameworks for GenAI applications.
Domain
Financial services / Payments / Anti-Money Laundering (AML)
Deliverable
production ML models
Required skills
Generative AI development (LLMs, diffusion models, transformers), RAG pipelines, Model Context Protocol (MCP), tool calling frameworks, LangChain/LangGraph, Python, PyTorch or TensorFlow, computer vision, MLOps, cloud platform integration (AWS, Azure), Databricks, prompt engineering, model fine-tuning, API development.
Preferred skills
Experience with observability tools for AI systems, knowledge of evaluation techniques for GenAI (hallucination detection, factuality scoring, bias evaluation).
Technologies
AWS, Azure, Databricks, LangChain, LangGraph, PyTorch, TensorFlow
Responsibilities
Implement generative AI models and applications for AML transaction monitoring use cases; Build advanced solutions leveraging RAG, MCP, tool calling, and LangChain/LangGraph for dynamic workflows; Develop machine learning pipelines for fine-tuning large language models and other foundation models; Implement content generation systems for text, image, and multimodal outputs; Apply computer vision techniques for image analysis, creative generation, and visual search; Implement evaluation frameworks for GenAI applications, including hallucination detection, bias checks, and quality scoring; Build observability and monitoring solutions for AI systems, including latency, cost tracking, and model performance metrics; Build scalable solutions on cloud platforms (AWS, Azure) and leverage data platforms like Databricks; Integrate AI models into production systems with a focus on performance, security, and compliance.
Seniority
Mid-level IC
