Description

You will build and maintain end-to-end machine learning pipelines covering the full lifecycle from ingestion to evaluation.

Responsibilities

• Develop ML pipelines encompassing data ingestion, transformation, training, validation, serving, and evaluation.
• Collaborate with AI scientists to productionize ML algorithms.
• Set up CI/CD/CT pipelines and model repositories.
• Deploy models as a service on both cloud and on-premise environments.
• Apply new tools and industry best practices to existing workflows.

Required Skills

• 8+ years of experience in machine learning or related fields.
• Proficiency in Python.
• Experience with GCP, Docker, and Kubernetes.
• Hands-on experience with Azure ML.
• Knowledge of task orchestration tools like MLflow, Kubeflow, Airflow, or Vertex AI.
• Competency in Linux/Unix environments, testing, and troubleshooting.
• Experience with Git, dependency management, and build tools such as GCP Cloud Build, Jenkins, GitLab CI/CD, or GitHub Actions.
• Familiarity with edge computing.
• Experience with WMS and Logistics.

Preferred Skills

• Data engineering experience using SQL, Kafka, GCP Dataflow, Beam, Spark, or Pandas.

Key Skills

Education

Any Graduate