AI/ML Engineer

Experience:

Role Overview

AI/ML Engineer

3 years of industry experience, including 1–2 years in AI/ML

Key Responsibilities

• Work with stakeholders to understand business requirements and translate them into ML problems.
• Collect, clean, and preprocess data for model development.
• Build and train machine learning models (classification, regression, clustering, etc.).
• Evaluate models using appropriate metrics and improve them through experimentation.
• Deploy trained models into production environments (basic API/web service or cloud deployment).
• Collaborate with data engineers and developers to integrate AI features into products.
• Document code, models, and experiments for future reference.
  

Technical Skills & Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, or related field.
• 3 years of total software/data experience, with 1–2 years focused on AI/ML projects.
• Solid programming skills in Python, with experience using ML libraries (scikit-learn, pandas, NumPy, TensorFlow/PyTorch basics).
• Experience building end-to-end ML models on real datasets (could be internal company projects or POCs).
• Familiarity with version control (Git) and working in a team environment.
• Strong problem-solving, communication, and willingness to learn advanced tools over time.
  

Nice-to-Have

• Exposure (not mastery) to cloud platforms (AWS/GCP/Azure) for hosting models.
• Basic understanding of containerization (Docker) or CI/CD pipelines.
• Some knowledge of data visualization (Matplotlib, Plotly) or dashboarding tools.
  

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