Senior Applied AI ML Engineer
Core
Design, build, and operate LLM solutions and risk feature data pipelines for AI-driven Global Financial Crimes Strategic Monitoring.
Role type
Senior Applied AI ML Engineer (Financial Crimes)
Builds
LLM solutions, risk feature data pipelines, and production-grade ML applications for detecting AML risk and regulatory violations.
Domain
Financial Services / AI / Natural Language Processing
Deliverable
production ML models
Required skills
Information retrieval, natural language processing, Python, Java, functional programming, JVM-based languages, PyTorch, TensorFlow, SciKit, NeMo, Hugging Face Transformers, AWS services, Databricks, SQL, NoSQL, messaging stacks, model serving, inference optimization
Preferred skills
Databricks CDAO platform, MLOps frameworks, AML monitoring and investigations systems, data engineering concepts, distributed systems, scalable architectures, vector databases
Responsibilities
Design, build, and run LLM solutions; create feedback and accuracy measurement methods for AI solutions; design, build, and operate risk feature data pipelines in Databricks; monitor for drift, bias, and performance degradation; alert on issues.
Seniority
Senior, hands-on IC
