MLOps Engineer with AWS cloud

MLOPS

office locations (Pittsburgh, PA, Cleveland, OH, Dallas, TX, Birmingham, AL or Phoenix, AZ,). 

 

Technical Skills:

o Amazon SageMaker: In-depth knowledge of SageMaker, including domain setup, configuration, and infrastructure management.

o Cloud Knowledge: A deep understanding of cloud computing concepts, especially related to Amazon Web Services (AWS).

o Infrastructure Design: Ability to design and implement MLOPs cloud solutions, considering scalability, security, and performance.

o Experience: Practical firsthand experience with cloud MLOps and Data Analytics platforms, preferably AWS SageMaker, Glue, EMR, Athena.

o Best Practices: Familiarity with best practices for MLOps and Data Engineering.

o EC2 Instances: Understanding of EC2 instance types and their suitability for AWS SageMaker.

o S3: Proficiency in using Amazon S3 for data storage and SageMaker input/output.

o IAM: Ability to manage permissions and access control using Identity and Access Management.

o Lambda: Knowledge of serverless computing for automating tasks.

o ML & Data Pipelines: Experience with creating data pipelines using AWS SageMaker services integrated with Glue and EMR.

o Monitoring and Troubleshooting: Proficiency in monitoring SageMaker cluster health, identifying bottlenecks, and resolving issues.

o Cost Optimization: Strategies to tag SageMaker resources with an eye on optimizing costs and observability.

Security and Compliance:

o Encryption: Understanding of data encryption at rest and in transit to ensure secure data analytics cloud environment.

o Security Groups and VPC: Knowledge of network security and virtual private clouds.

o Compliance Controls: Ensuring compliance with industry standards and regulations.

Scripting and Automation:

o Language Proficiency: Python, R, Spark, SQL in scripting languages for automating tasks.

o MLOPs: Ability to collaborate with the business to optimize MLOps process, and model lifeycle using SageMaker

o Infrastructure as Code (IaC): Ability to assist DevOps engineers to develop proper Terraform templates used to provision AWS analytics infrastructure.

Backup and Disaster Recovery:

o Snapshotting: Familiarity with taking EMR cluster snapshots for backup and recovery.

o High Availability: Implementing strategies for fault tolerance and disaster recovery.

Soft Skills:

o Communication: Effective communication with stakeholders, developers, and data engineers.

o Problem-Solving: Analytical thinking to address complex issues.

o Adaptability: Keeping up with evolving technologies and best practices.

o Decisiveness: Make informed decisions, especially when dealing with complex architectural choices.

o Business Acumen: Understand business requirements and align technical solutions accordingly.

o Continuous Learning: A zeal for staying updated with evolving cloud technologies.

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Experience and Certifications:

o Experience: Senior AWS Cloud Engineers must have 3 to 5 years of firsthand experience in designing and building cloud MLOps and Data Analytics applications.

o Certifications: AWS Professional Developer or Data certifications are desired for senior roles