Senior MLE

About the job

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 Surveillance platform that detects regulatory violations, insider risk, misconduct, and behavioral anomalies across enterprise communications and collaboration systems. As a Senior MLE on the team, you will design, build and productionize M ... L and LLM powered detection systems that operate at scale across high-volume communication streams. You will work at the intersection of Risk modeling, NLP and transformer architectures, near real-time inference systems, regulatory explainability and auditability. This is a hands-on senior role requiring deep expertise in applied NLP, 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 LLM powered features such as risk detection, alert explanation, conversation summarization, reviewer assisted co-pilots • Implement explainability techniques (SHAP, LIME, attention visualization) ensuring model outputs are traceable, versioned and reproducible • Optimize inference latency and token efficiency for production environments • Implement RAG and LLM based risk analysis pipelines processing data at web scale • Bake in augmentation mechanisms leveraging legacy regular expressions for filtering and optimization • Design real-time and batch processing and scoring pipelines (kafka/spark) • Implement experiment tracking, model versioning and CI/CD for ML • 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 • 8+ years experience in cloud based applications with 4+ years of experience as an MLE • Strong foundation in Information Retrieval, Natural Language Processing and • Expert in functional programming and JVM based languages- Python/Kotlin, 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 such as SageMaker, ECS, Lambda functions, Bedrock • 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.