Python AI/ML Engineer

Position:

Experience:

Location:

About the Role

Python AI/ML Engineer

Key Responsibilities

• Design, develop, and deploy

  machine learning models

  using Python.
• Build

  ETL pipelines

  for data preprocessing and feature engineering.
• Work with ML frameworks (

  TensorFlow, PyTorch, Scikit-learn

  ).
• Implement and optimize

  training, validation, and testing workflows

  .
• Collaborate with data engineers and scientists on model integration.
• Deploy models into production using

  APIs, Docker, or cloud services

  .
• Monitor model performance, retrain as needed, and ensure scalability.
• Implement

  MLOps best practices

  for automation and CI/CD pipelines.
• Document workflows and maintain reproducibility of experiments.

Required Skills & Qualifications

• 3–6 years of professional experience in

  Python development & ML

  .
• Strong knowledge of

  machine learning algorithms & data preprocessing

  .
• Proficiency with

  ML frameworks

  (TensorFlow, PyTorch, Scikit-learn).
• Hands-on with

  Pandas, NumPy, Matplotlib/Seaborn

  for data analysis.
• Experience with

  REST API development (Flask, FastAPI, Django)

  .
• Familiarity with

  cloud platforms

  (AWS Sagemaker, Azure ML, GCP AI).
• Experience with

  SQL/NoSQL databases

  for ML pipelines.
• Strong problem-solving and debugging skills.

Good to Have

• Exposure to

  LLMs (Hugging Face, OpenAI APIs, LangChain)

  .
• Experience with

  MLOps tools

  (MLflow, Kubeflow, Airflow).
• Knowledge of

  deep learning (NLP, CV)

  projects.
• Familiarity with

  Docker/Kubernetes

  .
• Cloud certifications (AWS, Azure, GCP ML/AI).