DevOps Engineers (ML/AI Ops)

Job Title: 

DevOps Engineer (with AI/MLOPS)

Job Experience Requirements:

• Bachelor’s degree in the areas of Computer Science, Engineering, Information Systems, Business, or equivalent field of study required.
• 5+ years of experience in working with data solutions (Data lakes, cloud data warehouses).
• 3+ years of experience developing data solutions on AWS.
• 2+ years Linux/Unix including basic commands, shell scripting and solution engineering.
• 2+ years of experience with S3, AWS Glue, EMR, MKS, RDS, Serverless technologies, DynamoDB, lambda, Kubernetes
• Strong knowledge of DevOps tools and practices (CI/CD, Infrastructure as Code, monitoring, etc.).
• Experience with AI/ML application technologies (LLM, Flask, Llama, Streamlit, ReactJs, etc) and frameworks (TensorFlow, LlamaIndex, LangChain etc.).
• Proficiency in scripting languages such as Python, Bash, Spark, Java with emphasis on tuning / optimization.
• Familiarity with containerization and orchestration technologies (Docker, Kubernetes).
• Strong critical thinking skills and ability to troubleshoot complex issues.
• Excellent communication skills and ability to work collaboratively in a team environment.
• Experience working with automated build and continuous integration systems (Chef, Jenkins, Docker, Github)
• Experience working with Data Governance , MDM tools is plus.

Job Responsibilities: 

• Contributing member of a high performing, agile team focused on next generation data & analytic technologies.
• Assist Data Engineering teams during design and development for highly complex and critical data projects.
• Code and integrate Platform solutions into the data analytic ecosystem.
• Experience in AWS environment operation and management, building AWS environments and using infrastructure as code.
• Design, implement, and maintain scalable and secure AWS infrastructure including AI/ML applications.
• Leveraging DevOps techniques and practices like CI/CD, Test Automation, Build Automation and Test-Driven Development to enable the rapid delivery of end user capabilities.
• Developing data solutions on cloud deployments collaborating with data scientists and engineers to deploy and manage AI/ML models in production environments.
• Works with Architects to design complex solutions and lead from inception to production.
• Creates and maintains DevOps processes, application infrastructure, and utilizes cloud services (including systems, network, and other administrative artifacts).
• Implement best practices for security, backup, and disaster recovery in AWS.
• Optimize cloud resource usage to manage costs effectively.
• Document and streamline operational processes to improve efficiency.
• Supporting Data Governance Tools and processes.