We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. We are building a next generation, AI-driven Global Financial Crimes Strategic Monitoring solutions that detects AML risk, regulatory violations, transactions risk, misconduct, and behavioral anomalies. As a Senior MLE on the team, you will design, build and productionize Risk typologies/ features, data pipelines, supervised and unsupervised ML models, and LLM risk explainability that operate at scale across high-volume banking transactions. You will work at the intersection of Risk modeling, and NLP architectures, inference systems, regulatory explainability and auditability. This is a hands-on senior role requiring deep expertise in ML operations, LLM integration, scalable ML systems and production grade engineering discipline. This role offers a chance to collaborate with product managers, architects, data science and operational teams, while also engaging in software engineering communities to explore new and emerging technologies. Job responsibilities • Design, build, collaborate, and operate ML models • Design, build and operate LLM solutions • Design and build feedback and accuracy measurement techniques for AI solutions • Design, build, and operate risk features data pipelines in Databricks • Conduct monitoring to detect and alert drift, bias and performance degradation • Work closely within a cross-functional team following agile based processes • Collaborate closely with Product Managers, SRE and Compliance SMEs to continuously improve product adoption, reliability and outcomes Required qualifications, capabilities, and skills • PhD in Computer Science, Data Science, AI or similar fields with with 2+ years of experience Or MS in Computer Science, Data Science, AI or similar fields with with 4+ years of experience or BS in Computer Science, Data Science, AI or similar fields with with 8+ years of experience • Strong foundation in Information Retrieval, Natural Language Processing and • Expert in functional programming and JVM based languages- Python, Java • Experience integrating models into cloud scale, microservices based architectures • Experience with one or more ML frameworks - Pytorch, Tensorflow, SciKit, NeMo, Huggingface Transformers • Hands-on experience with AWS services, and Databricks • Experience/Exposure to SQL, NoSQL and messaging stacks • Excellent verbal & written communication skills and bias for action and ownership in early stage env • Operational experience in supporting an enterprise grade ML application in production Preferred qualifications, capabilities, and skills • Knowledge of Firm Databricks CDAO platform is good to have • Experience with building production-grade ML pipelines, APIs and MLOps frameworks • Experience in AML, monitoring and investigations systems is a strong plus • Good understanding of data engineering concepts, distributed systems, and scalable architectures • Familiarity with vector databases, model serving, and inference optimization is a plus