Senior Applied AI ML Engineer

What you'll do

• Design, build, and operate ML models, LLM solutions, and risk-feature data pipelines in Databricks.
• Develop feedback and accuracy measurement techniques; monitor for drift, bias, and performance degradation.
• Collaborate with product, SRE, compliance, data science, and operations teams to improve reliability and outcomes.

What they ask for

• PhD in Computer Science, Data Science, AI, or similar with 2+ years of experience; or MS in those fields with 4+ years; or BS in those fields with 8+ years.
• Strong foundation in Information Retrieval and Natural Language Processing; expertise in functional programming and JVM-based languages, including Python and Java.
• Experience integrating models into cloud-scale, microservices-based architectures and supporting enterprise-grade ML applications in production.
• Hands-on AWS services and Databricks experience; experience with one or more listed ML frameworks and exposure to SQL, NoSQL, and messaging stacks.

Nice to have

• Knowledge of Firm Databricks CDAO platform; experience building production-grade ML pipelines, APIs, and MLOps frameworks.
• AML, monitoring, or investigations experience; familiarity with vector databases, model serving, or inference optimization.

Pay

USD 171,000.00-$260,000.00 base salary

Tools

Python, Java, Pytorch, Tensorflow, SciKit, NeMo, Huggingface Transformers, Databricks

AI focus

Develop and productionize ML models and LLM solutions for financial-crime risk detection, explainability, feedback and accuracy measurement, and ongoing monitoring.