3+ years of experience (post-PhD or during PhD/postdoc) developing production-grade ML/applied mathematics/Statistics/relevant field
Strong knowledge of statistical analysis, machine learning, and deep learning
.Developing advanced algorithms and models to extract valuable insights from complex datasets, with a focus on generative AI and large language models (LLMs)
Utilizing cloud-based AI services (e.g., AWS, Azure, GCP) to build scalable and efficient AI solutions.
Implementing MLOps, LLMOps, AgentOps practices for model or agent deployment, monitoring, and management.
.Conduct applied research in areas such as NLP, time-series, reinforcement learning, computer vision, or multimodal learning.
. Proficiency in Python or R, along with relevant libraries (e.g., pandas, NumPy, scikit-learn, TensorFlow, PyTorch).
Proficiency in production implementation of AI models in NLP, Vision, Forecasting streams.
Experience in developing and deploying AI/Gen AI based systems in production.
Knowledge of LangChain, Phoenix, MLFlow, LangGraph, Google Agent Development Kit
Publish articles/blogs in internal and external forums
Mentoring junior data scientists and providing technical guidance.
