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Open nowPosted 343 days ago

DevOps Engineer

withRemote

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11.5% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
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  2. 4.3%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: posted 343 days ago

The posting

DevOps & Data Engineer - ML Infrastructure & Analytics

## Company Overview Company information is not provided. Please include relevant details if available.

## Job Summary The DevOps & Data Engineer role focuses on designing and implementing a multi-tenant cloud infrastructure on AWS, while also deploying and scaling machine learning models. This position is critical for enhancing analytics capabilities and improving operational efficiencies by implementing best practices for MLOps and ensuring compliance and security across varying cloud environments.

## Responsibilities - Design and implement the multi-tenant cloud infrastructure on AWS. - Deploy and scale SaaS applications and SLM instances across GPU-enabled infrastructure. - Implement MLOps pipelines for model training, deployment, and monitoring. - Ensure security, compliance, and data isolation across tenants. - Set up monitoring, alerting, and performance optimization systems to maintain efficiency.

## Qualifications - Proven experience in deploying multi-tenant SaaS applications. - Production experience with data warehouse setup, specifically Amazon Redshift. - Experience in ML model deployment and scaling, or any AI model deployment experience. - Proficiency in Infrastructure as Code (IaC) tools and automation expertise. - Knowledge of security and compliance implementation strategies. - Experience in deploying and scaling a multi-tenant B2B SaaS platform. - Background in building data warehouses and ETL pipelines for analytics. - Familiarity with managing ML model deployment and inference serving, along with completing CI/CD implementation with security scanning.

### Educational Qualifications - Relevant degree in Computer Science, Engineering, or a related field preferred.

## Preferred Skills - Familiarity with Kubernetes and container orchestration. - Experience with monitoring tools such as Grafana, Datadog, CloudWatch, and the ELK Stack. - Understanding of security practices including VPC, IAM, encryption, and SOC 2 compliance.

## Experience - Minimum of 3-5 years of experience in DevOps and Data Engineering roles, with relevant experience in cloud infrastructure and machine learning systems.

## Environment - This position is remote, offering flexibility in work location. The working hours are from 5 PM to 2 AM, with a schedule from Monday to Saturday.

## Salary - Salary is estimated to be up to $100,000 per month, based on experience and skills.

## Growth Opportunities Potential career advancement opportunities may be available based on performance and project needs.

## Benefits Benefits information is not provided. Please include any relevant details if available.

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