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AI​/Data Engineers

Job in Bengaluru, 560001, Bangalore, Karnataka, India
Listing for: ERPMARK INC
Full Time position
Listed on 2026-02-21
Job specializations:
  • IT/Tech
    Data Engineer, AI Engineer, Machine Learning/ ML Engineer, Cloud Computing
Job Description & How to Apply Below
Position: 8 AI / Data Engineers
Location: Bengaluru

AI / Data Engineer

Role Summary
We are hiring  8 AI / Data Engineers  for LTIMindtree, Bangalore. This is a hands-on technical role focused on building, deploying, and optimizing AI/ML and data engineering solutions. Candidates must have strong real-time project experience in data pipelines, machine learning models, and cloud-based data platforms.

Key Responsibilities
Design, develop, and optimize scalable  data pipelines and ETL/ELT workflows
Build, train, and deploy  Machine Learning / AI models  in production environments
Work with structured and unstructured data using  Python and SQL
Implement data processing using  Spark / Py Spark
Deploy AI/ML solutions on  AWS / Azure / GCP
Develop APIs and integrate ML models into applications
Ensure data quality, performance tuning, and governance compliance
Collaborate with cross-functional teams in Agile environments
Must-Have (Mandatory) Skills
4+ years of strong hands-on experience in  AI / Machine Learning / Data Engineering
Proficiency in  Python  and  SQL

Experience with  Apache Spark / Py Spark
Strong experience in  ETL/ELT, Data Modeling, Data Warehousing
Hands-on experience with  AWS / Azure / GCP cloud services

Experience with  ML frameworks (Tensor Flow, PyTorch, Scikit-learn)
Working knowledge of  REST APIs and model deployment

Experience with  Databricks / Snowflake / Big Query / Redshift
Strong understanding of  data structures, algorithms, and statistics
Experience working in  Agile / Scrum environments
Experience Requirements
4–8 years of relevant industry experience in AI / Data Engineering roles
Proven hands-on project experience in enterprise-scale data platforms
Experience working with global clients or large enterprise environments preferred
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