Responsibilities

📍Work part-time or full-time during the year with the core Sentient Research team 📍Conduct cutting-edge generative AI research in a fast-paced environment 📍Design new agent architectures to improve end-to-end performance of AI workflows 📍Design, run, and evaluate experiments to improve LLMs on various benchmarks 📍Execute data engineering tasks to curate data for LLM pre-training, fine-tuning, RAG 📍Integrate and evaluate models with multi-modal capabilities for different verticals 📍Read conference papers on generative AI and knowledge retrieval to understand and evaluate new research in the space 📍Replicate, evaluate, and integrate theoretical data-curation approaches, fine-tuning algorithms, and agent architectures from research papers into real products 📍Set up fine-tuning and evaluation pipelines on AWS, GCP, and other compute providers 📍Manage AI workload compute resources and monitoring, keeping track of experiments and assessing results

Required Qualifications

📍Hands-on experience in generative AI research and/or engineering, whether in industry or through academic work during the Bachelor’s / Master’s / PhD degree with corresponding published work 📍Demonstrated expertise in deep learning and transformer models 📍Mastery of Python (PyTorch, numpy, agentic frameworks) for building AI workflows, fine-tuning models, and writing evaluations 📍Strong foundation in data structures, algorithms, and software engineering principles

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