MLOps Engineer

Overview

On Site
Hybrid
$55+
Full Time
No Travel Required
Able to Provide Sponsorship

Skills

Amazon EC2
Amazon SageMaker
Amazon Web Services
Apache Spark
Machine Learning (ML)
Machine Learning Operations (ML Ops)
SQL
Python

Job Details

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 Analtics 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 Langauge 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

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.

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.

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