Lead ML/AI Engineer

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