Job Description

Responsibilities


  • Develop and deploy advanced machine learning and deep learning models for real-world applications

  • Build and refine high-quality datasets, ensuring robustness and relevance

  • Conduct data analysis to guide model development and validate performance

  • Manage the end-to-end ML lifecycle — from training and tuning to validation and deployment

  • Implement MLOps practices (CI/CD, monitoring, automation)

  • Work with Python and core AI/ML libraries (e.g., PyTorch, TensorFlow, scikit-learn)

  • Containerize models using Docker for scalable deployment

  • For LLM applications: design and test prompts, evaluate outputs, and support data labeling and fine-tuning

  • Collaborate with Product Owners, Software Engineers, and QA teams to integrate AI models into production
  • Qualifications

  • Proven experience developing and deploying ML models in production
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