As a Lead Data AI/ML Engineer Vice President at Barclays, you will play a crucial role in shaping the future by spearheading the evolution of the Corporate Data Services function. Your responsibilities include:
Participating in daily stand-up meetings to discuss progress, blockers, and daily plans
Working on deploying AI/ML models into production environments using AWS services like Glue, Lambda, and Step Functions
Building and maintaining data pipelines using Spark and Python for seamless data flow and integration
Collaborating with data scientists, software engineers, and stakeholders to provide technical solutions
Monitoring and optimizing the performance of AI/ML models in production for efficiency and scalability
Documenting processes, workflows, and best practices for knowledge sharing and governance compliance
To excel in this role, you should have experience in data engineering, AI/ML model deployment, and working with AWS services like Glue, Lambda, and Step Functions. Additionally, you should possess strong skills in Apache Spark, Python programming, AI/ML model deployment, data engineering principles, and domain knowledge within the Financial Service environment. Qualifications required for this position include a bachelor's or master's degree in computer science, Data Engineering, or a related field. Relevant certifications such as AWS Certified Data Analytics Specialty or AWS Certified Machine Learning Specialty are also beneficial. Some highly valued skills for this role include familiarity with DevOps practices, knowledge of big data technologies like Hadoop and Kafka, experience with machine learning frameworks such as TensorFlow or PyTorch, and understanding of data governance and data quality. In this role, you will lead engineering teams effectively, oversee timelines, mentor team members, evaluate and enhance engineering processes, collaborate with stakeholders, and enforce technology standards. The location of the role is in Pune, IN. As a Lead Data AI/ML Engineer Vice President at Barclays, you will play a crucial role in shaping the future by spearheading the evolution of the Corporate Data Services function. Your responsibilities include:
Participating in daily stand-up meetings to discuss progress, blockers, and daily plans
Working on deploying AI/ML models into production environments using AWS services like Glue, Lambda, and Step Functions
Building and maintaining data pipelines using Spark and Python for seamless data flow and integration
Collaborating with data scientists, software engineers, and stakeholders to provide technical solutions
Monitoring and optimizing the performance of AI/ML models in production for efficiency and scalability
Documenting processes, workflows, and best practices for knowledge sharing and governance compliance
To excel in this role, you should have experience in data engineering, AI/ML model deployment, and working with AWS services like Glue, Lambda, and Step Functions. Additionally, you should possess strong skills in Apache Spark, Python programming, AI/ML model deployment, data engineering principles, and domain knowledge within the Financial Service environment. Qualifications required for this position include a bachelor's or master's degree in computer science, Data Engineering, or a related field. Relevant certifications such as AWS Certified Data Analytics Specialty or AWS Certified Machine Learning Specialty are also beneficial. Some highly valued skills for this role include familiarity with DevOps practices, knowledge of big data technologies like Hadoop and Kafka, experience with machine learning frameworks such as TensorFlow or PyTorch, and understanding of data governance and data quality. In this role, you will lead engineering teams effectively, oversee timelines, mentor team members, evaluate and enhance engineering processes, collaborate with stakeholders, and enforce technology standards. The location of the role is in Pune, IN.