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Job Description & How to Apply Below
You will work at the crossroads of data science, engineering, and cloud infrastructure to build scalable and automated AI systems that deliver business value.
Your role will involve collaborating with data scientists, stakeholders, and cloud engineers to turn AI experiments into stable and efficient applications. Join us to contribute to predictive analytics, generative AI solutions, and interactive dashboards that empower business leaders.
Responsibilities
Collaborate with data scientists to convert machine learning and generative AI experiments into scalable production pipelines
Develop and maintain shared code repositories and reusable components
Design and implement CI/CD pipelines in AWS or Azure for deploying models, APIs, and generative AI tools
Build and manage data pipelines and Data Ops processes
Containerize applications with Docker and deploy them on cloud-native platforms
Automate infrastructure provisioning using Terraform and manage database schemas in Azure and Snowflake
Deploy and operate generative AI applications such as chatbots, retrieval-augmented generation systems, and predictive analytics tools
Implement monitoring, observability, and explainability mechanisms to ensure system reliability
Establish alerting, rollback strategies, and observability tools to maintain system stability
Participate in code reviews and recommend improvements to workflows
Requirements
Extensive experience in MLOps and data integration with 5 to 9 years in related roles
Proven background in designing and deploying scalable machine learning production pipelines
Competency in cloud platforms such as AWS and Azure for infrastructure and model deployment
Skills in containerization technologies like Docker and infrastructure as code using Terraform
Familiarity with data orchestration and management in Azure and Snowflake environments
Knowledge of generative AI fundamentals and practical deployment experience
Ability to collaborate effectively with data scientists and engineers to operationalize AI models
Strong problem-solving skills and attention to system observability and reliability
Nice to have
Experience with large language models (LLM)
Understanding of retrieval-augmented generation (RAG) systems
Position Requirements
10+ Years
work experience
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