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Junior AI & Data Engineer

Summary

A junior AI & Data Engineer role focused on learning data engineering, ML fundamentals, and ETL pipelines under mentorship, working on Python/SQL-based projects for AI/ML initiatives.

This is a remote position.

We are hiring smart, analytical freshers and early‑career engineers for a Junior AI & Data Engineer role. This is a developmental position focused on building strong fundamentals in Data Science, Machine Learning, and Data Engineering.
You will support real‑world AI/ML initiatives and data pipelines under the mentorship of senior engineers and data scientists.
Key Responsibilities
  • Assist in data collection, cleaning, transformation, and analysis for AI/ML projects
  • Write clean and efficient Python code for ETL pipelines and feature engineering
  • Support development of basic ML models (regression, classification, clustering) under guidance
  • Create dashboards, reports, and visualizations for data insights
  • Document workflows, pipelines, and learnings
  • Learn and apply SQL best practices and cloud fundamentals (AWS/GCP/Azure)

Requirements

  • Strong Python skills (pandas, NumPy, basic scikit‑learn)
  • Good understanding of Statistics (mean, variance, correlation, regression)
  • Basic knowledge of Linear Algebra (vectors, matrices)
  • Exposure to SQL and relational databases
  • Strong logical and analytical thinking
  • Willingness to learn Machine Learning, MLOps, and Data Engineering
  • Ability to work in a fast‑paced, Agile environment
Good to Have / Preferred Skills
  • Exposure to cloud platforms (AWS, GCP, Azure)
  • Experience with ML models or Kaggle competitions
  • Familiarity with Jupyter Notebooks and basic REST APIs
  • Strong interest in mathematics + programming + problem‑solving
Soft Skills
  • Curiosity and eagerness to learn
  • Ownership and accountability
  • Ability to take feedback and improve rapidly
  • Clear communication and teamwork
  • Structured problem‑solving mindset

Benefits

  • Competitive compensation as per industry standards
  • Strong mentorship‑driven learning environment
  • Hands‑on exposure to enterprise AI & data problems
  • Clear growth path toward AI Engineer, ML Engineer, or Data Engineer roles
  • Collaborative, global, innovation‑focused culture

See also

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