AI Machine Learning Engineer

Job Profile : AI Machine Learning Engineer

Location : Pune

Experience :8-10years

Must Have Experience with MLOps processes and tools Experience with SQL, Databricks, MLFlow and PowerBI/Tableau.

Hands-on experience with MLOps tools and cloud ML platforms such as MLflow, Databricks, Azure ML, or equivalent.

Strong SQL and data analysis skills for validation, troubleshooting, monitoring, and reporting.

Experience with model lifecycle management, including model registry, versioning, lineage, reproducibility, deployment tracking, and monitoring.

Familiarity with dashboards and alerting tools such as Power BI, Tableau, Databricks SQL dashboards, or equivalent. Working knowledge of Git, CI/CD, scripting, and production support practices would be advantageous.

Analytical and pragmatic, with the ability to interpret governance principles into implementation plans Clear communicator who can explain complex technical risks and solutions to non-technical stakeholders.

Self-driven and proactive, comfortable working in a fast-paced environment.

Familiarity with ML and data development process in telco environment.

Bachelor’s or Master’s degree in Computer Science or a related field.

Key Responsibilities Responsible for designing, implementing, and managing MLOps workflows, tools, and operational processes for AIML solutions.

Oversee the day-to-day stability, reliability, and operational health of ML models and ML pipelines.

Manage model lifecycle operations, including model registration, versioning, deployment tracking, lineage, reproducibility, and governance.

Implement monitoring for data drift, concept drift, model performance degradation, inference quality, and service-level issues.

Develop and execute incident handling, recovery, rollback, and escalation plans for ML-related issues.

Required Skills Technical Skills: Hands-on experience with MLOps tools and cloud ML platforms such as MLflow, Databricks, Azure ML, or equivalent.

Strong SQL and data analysis skills for validation, troubleshooting, monitoring, and reporting.

Experience with model lifecycle management, including model registry, versioning, lineage, reproducibility, deployment tracking, and monitoring.

Familiarity with dashboards and alerting tools such as Power BI, Tableau, Databricks SQL dashboards, or equivalent.

Working knowledge of Git, CI/CD, scripting, and production support practices would be advantageous.

Non-Technical Analytical and pragmatic, with the ability to interpret governance principles into implementation plans

Clear communicator who can explain complex technical risks and solutions to non-technical stakeholders

Self-driven and proactive, comfortable working in a fast-paced environment

Other Task-Specific Knowledge

Familiarity with ML and data development process in telco environment