Note ::--- We are hiring for Accenture. If you have already applied through the Accenture Career Portal within the last 1 year, submitted an application, or appeared for an interview, please do not apply, IGNORE

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Strong understanding of AI/ML concepts and the compute, storage, networking, security and deployment foundations required to run AI workloads.
Minimum 2 years of proficiency in programming or scripting languages such as Python, Java, C++, Bash or PowerShell.
Experience with CI/CD, infrastructure-as-code, containers, Kubernetes, workflow orchestration and operational monitoring tools.
Solid problem-solving ability, communication skills and collaboration mindset in a fast-paced engineering environment.
Required Skills/ Experience




Hands-on experience with Databricks workspaces, clusters, jobs, notebooks, MLflow, model registry, feature engineering workflows and cloud storage integrations.
Experience designing or operating scalable data and ML pipelines, distributed processing workloads, model-serving patterns and production ML operations.
Working knowledge of Python, SQL, Spark, Terraform/Databricks Asset Bundles, Git-based CI/CD and observability practices.
Ability to optimize clusters, jobs and pipelines for performance, reliability, scalability, cost and security.
Understanding of MLOps patterns including experiment tracking, model registry, model deployment, monitoring and rollback approaches.

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