Senior ML Engineer

Responsibilities

• Manage Data : Extract, clean, and structure both structured and unstructured data.
• Coordinate Pipelines : Utilize tools such as Airflow, Step Functions, or Azure Data Factory to orchestrate data workflows.
• Deploy Models : Develop, fine-tune, and deploy models using platforms like SageMaker, Azure ML, or Vertex AI.
• Scale Solutions : Leverage Spark or Databricks to handle large-scale data processing tasks.
• Automate Processes : Implement automation using tools like Docker, Kubernetes, CI / CD pipelines, MLFlow, Seldon, and Kubeflow.
• Collaborate Effectively : Work alongside engineers, architects, and business stakeholders to address and resolve real-world problems efficiently.

Qualifications

Preferred Qualifications

Skills : sql,kubeflow,spark,docker,databricks,ml,gcp,mlflow,kubernetes,aws,pytorch,azure,ci / cd,tensorflow,scikit-learn,seldon,python,mlops

Skills Required

Airflow, Step Functions, Sql, Tensorflow, Azure ML, Azure Data Factory, Pytorch, Gcp, Docker, Spark, Databricks, Azure, Kubernetes, Python, Aws