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Job Title:

Applied Scientist

Company: Meril

Location: Bengaluru, Karnataka

Created: 2026-01-26

Job Type: Full Time

Job Description:

Applied ScientistLocation: Bangalore / HybridTeam: AIRole OverviewWe are seeking an Applied AI Scientist to work on end-to-end applied research and build scalable AI systems using Machine Learning, Deep Learning, and Large Language Models (LLMs). This role focuses on transforming complex problems into practical, high-impact solutions through research, experimentation, and engineering.Key Responsibilities- Design and execute applied research projects using ML, DL, and LLM techniques - Collaborate with cross-functional teams to define open-ended problems and deliver data-driven solutions - Develop, prototype, and optimize models on large-scale structured and unstructured datasets - Contribute to internal research infrastructure, tools, and model deployment pipelines - Stay up to date with advancements in AI research and industry best practices - Translate research findings into reliable, production-ready systemsWhat You’ll Gain- Exposure to real-world applied AI challenges with measurable impact - Access to large datasets and high-performance computing resources - A collaborative environment that values research rigor and innovation - Opportunities for mentorship, knowledge sharing, and professional growth - Support for publishing, open-source contributions, and external collaborationsQualifications- PhD or Master’s degree in Computer Science, Applied Mathematics, Statistics, Physics - 3+ years of experience building ML, DL, RL, or LLM-based systems in research or industry - Strong foundation in statistics, optimization, and numerical methods - Experience with time-series modeling, NLP, or high-dimensional data - Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, JAX, or Hugging Face - Familiarity with distributed training, MLOps practices, and version control (Git) - Strong communication and collaboration skillsPreferred Qualifications- Publications in leading AI conferences (NeurIPS, ICML, ICLR, KDD, etc.) - Experience working with large-scale or noisy datasets - Background in applied research environments

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