Leading AI Research Scientist

8 hours ago

Bellary, Karnataka, India beBeeMachineLearning Full time ₹ 15,00,000 - ₹ 25,00,000

Job Opportunity:

We are seeking a talented AI Research Scientist to join our team. As an AI Research Scientist, you will play a key role in designing and executing machine learning experiments to evaluate emerging AI technologies and frameworks.

About the Role:

  • You will be responsible for prototyping and assessing end-to-end AI solutions to inform product and platform strategy.
  • Designing and executing machine learning experiments to evaluate emerging AI technologies and frameworks.
  • Formulating hypotheses and conducting structured evaluations to compare technical approaches.
  • Applying modern ML engineering practices to build and test scalable, modular proof-of-concept systems.
  • Contributing to the definition of best practices for experimentation, evaluation, and technical decision-making.
  • Synthesizing and communicating experimental results to guide investment and adoption decisions.
  • Translating new research ideas and tools into functional, decision-relevant demonstrations.
  • Operating independently while contributing to a highly collaborative team environment.
  • Communicating technical findings clearly and concisely to both technical and non-technical audiences.

Requirements:

  • Bachelor's degree in computer science, data science, information technology, statistics, economics, or a related STEM field.
  • 3+ years of experience building machine learning-powered applications or tooling.
  • Strong proficiency in Python and familiarity with modern ML/AI libraries (e.g., PyTorch, Hugging Face, OpenAI SDKs).
  • Experience working with LLM orchestration or agent frameworks.
  • Understanding of model tuning, prompt engineering, or retrieval-augmented generation (RAG) patterns.
  • Experience developing and deploying applications in cloud environments (e.g., AWS, GCP, or Azure), including use of Docker and/or Kubernetes.
  • Demonstrated ability to independently prototype, test, and iterate on technical ideas.
  • Familiarity with ML evaluation techniques and structured experimentation workflows.
  • Proficiency with version control systems, CI/CD practices, and ML observability tools.

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