Advanced AI Research and Development Position

15 hours ago

Thiruvananthapuram, Kerala, India beBeeInnovation Full time ₹ 25,00,000 - ₹ 40,00,000
Senior AI Researcher Opportunity

This role offers a unique blend of cutting-edge AI research and hands-on system development, enabling you to conduct in-depth research, build, validate, and deploy groundbreaking AI capabilities from start to finish.

You will serve as a bridge between scientific theory and software implementation. Your tasks will include innovating on Large Language Models (LLMs), prompt systems, evaluation frameworks, and algorithm pipelines, with the goal of bringing these innovations to production-grade systems that impact real users.

  • Design and execute experiments in LLM training, LLM agent architectures, fine-tuning, reinforcement learning, and new evaluation methodologies.
  • Develop and test code-first prototypes to validate hypotheses and iterate rapidly, then refactor them into robust production systems when experiments are successful.
Key Responsibilities

Research Prototyping:

  • Tackle complex problems in LLM training, LLM architecture, fine-tuning, reinforcement learning, and new evaluation methodologies.
  • Build high-quality prototypes to test hypotheses and refine them for production-readiness.

Model & Architecture Innovation:

  • Develop and benchmark improvements in LLM architecture, fine-tuning workflows, and generation control.
  • Optimize models for performance, resource efficiency, and interpretability.

Production Engineering:

  • Own infrastructure: data pipelines, experiment sandbox, model serving, batch/online inference, logging, and CI/CD.
  • Treat experiments as software: automated testing, clear versioning, reproducibility, and documentation.

Scientific Experiment Tooling:

  • Create frameworks to automate scientific cycles: data generation, metric computation, model comparison dashboards.
  • Enable internal teams to run reproducible experiments at scale.

Knowledge Sharing & Publication:

  • Write up interesting findings—internal memos, tech blogs, or scholarship-worthy results.
  • Participate in code and science critique sessions with peers.

Qualifications

  • Master's or Ph.D. in Computer Science, Machine Learning, or related field (or equivalent experience)
  • Deep familiarity with LLMs, fine-tuning, reinforcement learning
  • Expertise in Python + frameworks like PyTorch or JAX; experience with Hugging Face or deployed LLM APIs
  • Strong software engineering skills: modular design, CI/CD, containerization, automated testing
  • Demonstrated track record in both research and production settings
  • Bonus: familiarity with Kubernetes, JAX compiler stacks (e.g., Flax, Alpa), Hugging Face Accelerate, or MLOps toolchains

Success Metrics

  • Research innovation: prototypes demonstrating clear scientific advances (e.g., better evaluation metrics or prompt robustness). Papers submitted or draft-ready internal research documents.
  • Engineering quality & velocity: experimental pipelines and prototypes are production-ready within sprint cycles; clean codebases, smooth deployments, few bugs.

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