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MLOPS Architect Machine Learning AI Architect at Remote for long term Contract at Remote, Remote, USA
Email: [email protected]
From:

Jayasurya tanuku,

Yochana IT

[email protected]

Reply to:   [email protected]

Hello, 

 Hope you are doing Well! 

I'm currently staffing for an MLOPS Architect (Machine Learning / AI Architect)
at Remote
.
Below you will find the job description, if you are qualified and interested please send me your Updated Word Document Resume to [email protected].   

My apologies if this position is not an ideal fit, we'll keep you in mind for other suitable positions and referrals would be appreciated. 

Thank you in advance. 

Role: MLOPS Architect (Machine Learning / AI Architect)

Location: Remote 

Duration: Long term contract on C2C/W2 

AWS, Python, Airflow, Kedro, or Luigi

Hadoop, Spark, or similar frameworks. Experience with graph databases a plus.

1.            Designing Cloud Architecture:

As an AWS Cloud Architect, youll be responsible for designing cloud architectures, preferably on AWS, Azure, or multi-cloud environments.

Your architecture design should enable seamless scalability, flexibility, and efficient resource utilization for MLOps implementations.

2.            Data Pipeline Design:

Develop data taxonomy and data pipeline designs to ensure efficient data management, processing, and utilization across the AI/ML platform.

These pipelines are critical for ingesting, transforming, and serving data to machine learning models.

3.            MLOps Implementation:

Collaborate with data scientists, engineers, and DevOps teams to implement MLOps best practices.

This involves setting up continuous integration and continuous deployment (CI/CD) pipelines for model training, deployment, and monitoring.

4.            Infrastructure as Code (IaC):

Use tools like AWS CloudFormation or Terraform to define and provision infrastructure resources.

Infrastructure as Code allows you to manage your cloud resources programmatically, ensuring consistency and reproducibility.

5.            Security and Compliance:

Ensure that the MLOps architecture adheres to security best practices and compliance requirements.

Implement access controls, encryption, and monitoring to protect sensitive data and models.

6.            Performance Optimization:

Optimize cloud resources for cost-effectiveness and performance.

Consider factors like auto-scaling, load balancing, and efficient use of compute resources.

7.            Monitoring and Troubleshooting:

Set up monitoring and alerting for the MLOps infrastructure.

Be prepared to troubleshoot issues related to infrastructure, data pipelines, and model deployments.

8.            Collaboration and Communication:

Work closely with cross-functional teams, including data scientists, software engineers, and business stakeholders.

Effective communication is essential to align technical decisions with business goals.

Responsibilities:

Strong experience in Python

Experience in data product development, analytical models, and model governance

Experience with AI workflow management tools such as Airflow, Kedro, or Luigi

Exposure statistical modeling, machine learning algorithms, and predictive analytics.

Highly structured and organized work planning skills

Strong understanding of the AI development lifecycle and Agile practices

Proficiency in big data technologies like Hadoop, Spark, or similar frameworks. Experience with graph databases a plus.

Extensive Experience in working with cloud computing platforms - AWS

Proven track record of delivering data products in environments with strict adherence to security and model governance standards.

Thanks & Regards,

Jayasurya,

Resource Specialist,

Yochana IT Solutions INC,

Farmington Hills, MI,

[email protected]

LinkedIn:
https://www.linkedin.com/in/jayasurya-t-81a094158/

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Keywords: continuous integration continuous deployment artificial intelligence machine learning information technology wtwo Michigan
MLOPS Architect Machine Learning AI Architect at Remote for long term Contract
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Tue May 07 03:06:00 UTC 2024

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