Data & Ai Professional 7 to 12 Years Pan India - Bengaluru, India - Capgemini Invent

Capgemini Invent

Verified Company

Bengaluru, India

2 weeks ago

Posted by:

Deepika Kaur

beBee Recuiter

Primary Skills-:

Cloud Platform: Azure/AWS/GCP
Data & AI Developer/Architect to support client engagements.
Experience with data life cycle management, governance, and standard engineering practices
Familiarity with Data & AI strategies, architectural patterns and microservices
MLOps & DevOps experience includes CI CD, ML Pipeline, Infrastructure as Code, Container Orchestrator, and ML Inference Part.
Should have atleast 2 implementation experience on Batch or Real time Data & AI related projects.

Job Responsibilities-:

Lead the design and implementation of data pipelines for collecting, cleaning, and analysing large datasets from various sources such as Sensors, Machines, and ERP systems.
Develop and maintain advanced machine learning models to optimize production processes, predict maintenance needs, and identify potential defects.
Collaborate with crossfunctional teams to identify business problems and opportunities that can be addressed with data and analytics.
Develop and maintain dashboards and visualizations to communicate insights to stakeholders and lead the data science team in creating and delivering presentations and reports.
Continuously monitor and evaluate model performance and make improvements as necessary.
Developing and maintaining the infrastructure and tools needed to deploy and manage machine learning models, including containerization, orchestration, and monitoring systems.
Building and maintaining automated pipelines for training, testing, and deploying machine learning models.
Experience with cloud platforms such as AWS, GCP, or Azure and Databricks is mandatory. Strong knowledge of scripting languages such as Python, and Linux system administration is required.
Experience in integrating APIs to front end stacks such as React Js etc.
Knowledge of big data processing technologies such as Hadoop, Spark, NoSQL DB, etc.