AI Engineer

AI Engineer

Job Category: Engineering
Job Type: Full Time
Job Location: Remote

About the Role:

We are looking for a passionate and experienced AI Engineer to join our team. You will be responsible for designing, developing, and deploying AI and machine learning solutions to solve real-world problems and improve business operations. You’ll work closely with data scientists, software engineers, and product teams to bring AI-powered features into production.


Key Responsibilities:

  • Deploy models using cloud platforms (AWS/GCP/Azure) and containerization tools like Docker/Kubernetes.
  • Develop, train, and optimize machine learning models for classification, regression, NLP, computer vision, or recommendation systems.
  • Design and implement AI-driven applications using frameworks like TensorFlow, PyTorch, or Hugging Face.
  • Work with large datasets: data preprocessing, feature engineering, and data augmentation.
  • Collaborate with cross-functional teams to integrate ML models into production-ready systems.
  • Evaluate and tune model performance using appropriate metrics.
  • Stay updated with the latest AI/ML research and apply new techniques to current projects.
  • Develop RESTful APIs to serve AI models in production.

Required Skills & Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.
  • Solid understanding of machine learning algorithms, deep learning architectures, and statistical modeling.
  • Proficiency in Python and ML libraries like Scikit-learn, Pandas, NumPy, TensorFlow, PyTorch, etc.
  • Experience with NLP, computer vision, or time series modeling is a plus.
  • Strong problem-solving skills and ability to write clean, efficient code.
  • Familiarity with MLOps tools and CI/CD pipelines for model deployment.
  • Knowledge of version control tools (e.g., Git).

Preferred Qualifications:

  • Experience with cloud services (AWS SageMaker, GCP Vertex AI, Azure ML).
  • Experience with real-time data processing tools (Kafka, Spark).
  • Understanding of data privacy, security, and ethical AI practices.
  • Contributions to open-source AI projects or research papers are a plus.

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