| Lead ML Ops Engineer : Hybrid - Irving, TX : USC GC GC EAD at Irving, Texas, USA |
| Email: [email protected] |
| From: Vivek Paliwal, kpg99 [email protected] Reply to: [email protected] MENTION VISA AND LOCATION Local to TX (USC/GC/GC EAD) Role : Lead ML/Ops Engineer Location : Hybrid - Irving, TX Duration : Long term Visa : USC, GC,GC EAD Job Description: Able to do in-person Interview - Final Round. Day to Day: This person will take the base code model that has been developed by the Data Science team and will be responsible to scale it,deploy it in a more reusable way, and manage the pipeline. Required: * Python & SQL for scripting & programming * Knowledge of ML & Ops Engineering * Open source (but they use Python on Azure Kubernetes) * Kubernetes * Public Cloud * 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/BigQuery, 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 Keywords: artificial intelligence machine learning information technology green card Texas Lead ML Ops Engineer : Hybrid - Irving, TX : USC GC GC EAD [email protected] |
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| Thu Sep 19 19:46:00 UTC 2024 |