Title: ML Ops Engineer Location: Alpharetta, GA (onsite form Day 1 (5 days)) Responsibilities • 8+ years’ experience of applied machine learning/ML Ops in BFS / Investment Management industry • PhD or MS in Computer Science, Statistics or related field • Expertise in Machine Learning algorithms and frameworks: · Training and tuning pre-trained models · Working with structured and unstructured for Fraud models • Deep proficiency in Python with experience developing production-quality Python modules • Strong domain focus on fine-tuning and enhancing fraud detection models • Deploying models in AWS production environments • Strong command on AWS cloud stack with working knowledge of architecture components i.e., SageMaker, Bedrock, Lambda, Lex, CloudWatch, CloudTrail, Redshift ML, DynamoDB, CodeBuild, CodeDeploy, S3, EC2, IAM, AMIs • Proficient in API development using Fast API, Flask, etc. delivering asynchronous AI inference services and scalable API solutions for AI-powered applications. · Roles and Responsibilities: • Work closely with Onsite Lead, Data scientists, Data Engineers, and QA and client stakeholders. • Evaluate input data for various statistical properties i.e., data drift using PSI and other metrics • Skilled in evaluation metrics like precision, recall, F1-score, and AUC-ROC, ensuring high accuracy and precision in classification and regression models for Fraud. • Ensure right-fitting of architecture in AWS for the models at hand to optimize model inferencing • Strong working command of AWS SageMaker, MLFlow, and CloudWatch is a must • Should have hands on experience with deploying CI/CD Pipelines in AWS • Assist with documentation and governance of all ML and NLP pipeline artifacts Note – VBeyond is fully committed to Diversity and Equal Employment Opportunity.