Meril is seeking an Applied Scientist to join a high-impact ML/LLM/DL research team in Bengaluru. This hands-on role involves designing and executing end-to-end ML/DL/LLM research projects, building predictive models, and applying Reinforcement Learning to complex dynamic systems to influence real-time, scalable ML systems.
About the role
About the Role
We are seeking exceptional Applied Scientists to join a high-impact ML/LLM/DL research team working on advanced large-scale modeling challenges. This is a hands-on research role where you will independently drive end-to-end initiatives from conceptualization and experimentation to production deployment. Your work will directly influence real-time, scalable ML systems.
Key Responsibilities
Design and execute end-to-end applied ML/DL/LLM research projects
Build predictive and signal extraction models using large-scale datasets
Apply Reinforcement Learning and deep learning techniques to complex dynamic systems
Prototype, validate and optimize models in scalable computing environments
Translate research outcomes into robust, production grade systems
Qualifications
PhD or Master’s degree in Computer Science, Mathematics, Statistics, Physics, or a related quantitative discipline
3+ years of applied experience in ML, RL, LLM or DL systems
Strong expertise in time-series forecasting, probabilistic modeling and natural language processing
Publications in leading conferences (NeurIPS, ICML, ICLR, KDD, UAI) preferred
Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, JAX or Hugging Face
Experience with distributed training, version control (Git) and MLOps best practices
Experience working with high-dimensional, noisy datasets
Mandatory Requirement
Strong foundation in Mathematics, Statistics, Probability and Stochastic Processes.
Skills
MLLlmDLReinforcement Learningtime series forecastingprobabilistic modelingNatural Language ProcessingPythonPyTorchTensorFlowJaxHugging FaceDistributed TrainingGitMlopsmathematicsStatisticsProbabilityStochastic Processes