Machine Learning Engineer

We're seeking a Senior Software Engineer for our Product Development team, building large-scale, cloud-based big data and MLOps platforms and APIs that integrate diverse data sources across a leading data and analytics organization's products and delivery channels.Requirements:BS in Computer Science or related field; MS preferred7-8 years' experience in engineering roles (software engineer, technical lead)3-4+ years' AWS experience architecting scalable, secure, cost-effective cloud-native solutionsAgile/scrum experienceKnowledge of AWS Well-Architected Framework and cloud best practicesMLOps platform experience (SageMaker, Kubeflow, or MLflow)- MANDATORYPython development experience (Flask, Django, AsyncIO)-MANDATORYDistributed systems experience: integration, testing, troubleshooting, monitoring, error recoveryAPI, real-time systems, and microservices design experienceAWS services experience (EKS, S3, RDS, Lambda, Aurora, ECS-Fargate)CI/CD tools familiarity (CodeCommit, CodeDeploy, CodePipeline, Jenkins, Harness)Async messaging/queue experience (Kafka, RabbitMQ, SQS)Strong problem-solving, analytical, and communication skillsEffective in fast-paced, globally distributed team environmentsResponsibilities:Design scalable, resilient cloud architectures with Architecture/Product/CloudOps/Engineering teams using AWS best practicesBuild ML pipelines using Python, AWS (SageMaker, Lambda, Step Functions, S3, ECR), and containers (Docker, ECS/Fargate)Contribute to design reviews and technical documentationEnsure code quality through testing and code reviewsCommunicate technical decisions to product and delivery teamsDrive quality/efficiency improvements via defect prevention and root cause analysisPrototype new technology integrationsSupport business requirement analysis with product teamsTune performance of existing and new systemsNice to have: Dynatrace/Splunk, TensorFlow/PyTorch/scikit-learn, Kubeflow/MLflow/Airflow, automated analytical pipelines