Artificial Intelligence Developer

12 hours ago

Mysore, Karnataka, India beBeeMachine Full time US$ 2,00,000 - US$ 2,50,000
Artificial Intelligence Developer

We are seeking a skilled Artificial Intelligence Developer to lead the development and deployment of scalable AI solutions. The ideal candidate will have a strong foundation in machine learning, graph algorithms, and SQL.

  • Develop and optimize machine learning models using Python libraries such as TensorFlow, PyTorch, or scikit-learn.
  • Design and implement graph-based algorithms and data structures using libraries like NetworkX or PyG for applications such as network analysis, fraud detection, or knowledge graphs.
  • Write complex SQL queries to manage, transform, and analyze large datasets, ensuring efficient data pipelines and integration with databases like PostgreSQL, MySQL, or SQLite.
  • Implement generative AI models (e.g., LLMs, GANs, or VAEs) using frameworks like Hugging Face, LangChain, or custom solutions for tasks such as text generation, data augmentation, or synthetic data creation.
Requirements
  • Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, or a related field.
  • 5+ years of professional Python programming experience.
  • 3+ years of hands-on experience in machine learning model development and deployment.
  • Proven expertise in graph algorithms, graph databases (e.g., Neo4j), or graph-based machine learning.
  • Strong proficiency in SQL and relational database management.
Technical Skills:
  • Expert-level Python programming (e.g., Pandas, NumPy, scikit-learn, TensorFlow, PyTorch).
  • Experience with graph libraries (e.g., NetworkX, PyG, or DGL) and graph databases.
  • Advanced SQL skills for querying and optimizing large datasets.
  • Familiarity with generative AI frameworks (e.g., Hugging Face, LangChain, or OpenAI APIs).
Preferred Qualifications
  • Experience with large-scale distributed systems and big data frameworks (e.g., Spark, Hadoop).
  • Familiarity with MLOps tools (e.g., MLflow, Kubeflow) for model lifecycle management.
  • Knowledge of advanced graph algorithms (e.g., community detection, shortest path, centrality measures).

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