Description

Lead the architecture, design, and implementation of end-to-end ML workloads from proof of concept to production.

Responsibilities

• Architect and implement scalable AI/ML solutions and data warehouse systems on cloud platforms.
• Provide technical guidance to architects and ML engineers on AI/ML methodologies and best practices.
• Drive research activities to explore new technologies, techniques, and processes in the field.
• Establish rigorous testing, validation, and monitoring processes to ensure model performance and reliability.
• Collaborate with cross-functional teams and business stakeholders to align AI/ML integration with business goals.

Required Skills

• 14-20 years of experience in analytics, solutioning, and technical roles.
• 5+ years of experience delivering ML/AI workloads on GCP, AWS, or Azure.
• Expertise in distributed computing and enterprise environments including Hadoop and Cloud platforms.
• Proficiency with data integration and ETL technologies such as Spark, PySpark, Scala, Dataflow, Dataproc, or EMR.
• Experience with traditional ETL tools like Informatica, DataStage, OWB, or Talend.
• Deep knowledge of databases including Cloud SQL, Cloud Spanner, Big Table, RDS, Aurora, DynamoDB, Oracle, Teradata, MySQL, DB2, or SQL Server.
• Exposure to NoSQL databases such as MongoDB, CouchDB, Cassandra, or Graph DB.
• Experience designing scalable data warehouse solutions using BigQuery or Redshift.

Preferred Skills

• Any Graduate degree.

Key Skills

Education

ANY GRADUATE