Job Description: Position Summary: As a Lead ML/AI Engineer, you will drive the design and implementation of functionality related to the end-to-end ML/AI and Feature lifecycle management on Azure/Google Cloud Platform, leveraging and integrating the cloud native services with other standard operational and automation tools. Key responsibilities include: • Support the deployment of ML/AI pipelines on the platform. • Enable functionality to support analysis, model optimization, statistical testing, model versioning, deployment and monitoring of model and data. • Ability to translate functionality into scalable, tested, and configurable platform architecture and software. • Establish strong software engineering principles for development in Python on the Azure/Google Cloud Platform. • Deliver features aligned to enterprise AutoML, Feature Engineering, and MLOPS capability. • Innovative thinking and great communication skills. • Strong ownership of deliverables, with design decisions aligned to scale and industry best practices. • Provide technical leadership and mentorship to a team of machine learning engineers. Collaborate with cross-functional teams to align ML initiatives with overall business goals. • Design, implement, and optimize machine learning algorithms and models. Stay abreast of the latest advancements in ML research and apply them to solve complex business problems. • Architect and implement scalable and efficient machine learning systems. Collaborate with software engineers to integrate ML models into production systems. • Work closely with data engineers to ensure the availability and quality of data for training and evaluation of machine learning models. • Develop strategies for deploying machine learning models at scale. Ensure models are integrated into production systems with high reliability and performance. • Design and conduct experiments to evaluate the performance of machine learning models. Iterate on models based on feedback and evolving business requirements. Required Qualifications: • 6+ years of experience in analytics domains, and deep understanding of ML operationalization and lifecycle management. • 5+ years of deploying and monitoring analytical assets in batch/real-time business processes. • 5+ years of SQL & Python programming experience leveraging strong software development principles. • Experience in designing and developing AI applications and systems. • Experience with real-time and streaming technology (i.e. Azure Event Hubs, Azure Functions, Pub/Sub, Kafka, Spark Streaming etc.) • Experience with REST API/Microservice development using Python/Java. • Experience with deployment/scaling of apps on containerized environment (AKS and/or GKE) • Experience with Snowflake/Big Query, Google Dataproc/Databricks or any big data frameworks on Spark • Experience with RDBMS and NoSQL Databases and hands-on query tuning/optimization. Preferred Qualifications: • Hands on experience in building solutions using cloud native services (Azure, GCP preferred) • Understanding of DevOps, Infrastructure as Code, automation for self service Education: • Required: bachelors degree in computer science, Engineering, Statistics, Physics, Math, or related field or equivalent experience • Preferred: masters degree or PhD with coursework focused on advanced algorithms, mathematics in computing, data structures, etc.