| Need 12+ years of Machine Learning Engineer - Remote - Nike - Long Term Contract at Remote, Remote, USA |
| Email: [email protected] |
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From: Saiteja, Aspired Solutions [email protected] Reply to: [email protected] Hi, Hope you are doing well. Role: Machine Learning Engineer/Data Engineer Location: Remote Duration: Long Term We are seeking an experienced Data Engineer/Machine Learning Engineer to lead the migration of workloads from AWS SageMaker to Databricks. The ideal candidate will have deep expertise in AWS SageMaker, Databricks, and MLOps, with a strong background in cloud-based machine learning and data engineering. Key Responsibilities: Assess and analyze existing AWS SageMaker workloads, including machine learning models, pipelines, and dependencies. Design and implement a scalable migration strategy to transition workloads from SageMaker to Databricks. Refactor and optimize ML models, feature engineering, and data pipelines for performance and cost-efficiency on Databricks. Ensure compatibility by modifying existing SageMaker scripts, Jupyter notebooks, and APIs for Databricks runtime. Migrate data pipelines from AWS services (S3, Glue, Athena, Redshift) to Databricks Delta Lake and Unity Catalog. Leverage Databricks capabilities (MLflow, AutoML, Feature Store) to enhance model training, deployment, and monitoring. Work with cross-functional teams, including data scientists, engineers, and DevOps, to ensure a smooth transition. Optimize compute costs by implementing best practices for Databricks clusters and resource allocation. Develop automation scripts for CI/CD and MLOps using Terraform, Git, and Databricks Workflows. Provide documentation and training to teams for managing workloads in Databricks. Required Skills & Qualifications: 7+ years of experience in Data Engineering or Machine Learning Engineering. Strong expertise in AWS SageMaker (training, inference, pipelines, feature store). Experience with Databricks, including MLflow, Delta Lake, and distributed computing. Proficiency in Python, PySpark, SQL, and hands-on experience with ETL workflows. Deep knowledge of AWS services (S3, Lambda, Glue, Redshift, Step Functions). Hands-on experience with Databricks Workflows, AutoML, Feature Store, and MLflow tracking. MLOps and CI/CD experience with tools like Terraform, GitHub Actions, or Jenkins. Strong problem-solving and debugging skills for optimizing ML workflows. Excellent communication skills and ability to work in a collaborative environment. Preferred Qualifications: Experience in migrating ML workloads between cloud platforms. Familiarity with Apache Spark, Kubernetes, and Databricks SQL. Knowledge of financial services, healthcare, or other data-intensive domains. Thanks, [email protected] Saiteja. Keywords: continuous integration continuous deployment machine learning sthree Need 12+ years of Machine Learning Engineer - Remote - Nike - Long Term Contract [email protected] |
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| 11:24 PM 27-Feb-25 |