Job Description
<h3>π Description</h3> β’ Work part-time or full-time during the year with the core Sentient Research team
β’ Conduct cutting-edge generative AI research in a fast-paced environment
β’ Design new agent architectures to improve end-to-end performance of AI workflows
β’ Design, run, and evaluate experiments to improve LLMs on various benchmarks
β’ Execute data engineering tasks to curate data for LLM pre-training, fine-tuning, RAG
β’ Integrate and evaluate models with multi-modal capabilities for different verticals
β’ Read conference papers on generative AI and knowledge retrieval to understand and evaluate new research in the space
β’ Replicate, evaluate, and integrate theoretical data-curation approaches, fine-tuning algorithms, and agent architectures from research papers into real products
β’ Set up fine-tuning and evaluation pipelines on AWS, GCP, and other compute providers
β’ Manage AI workload compute resources and monitoring, keeping track of experiments and assessing results <h3>π― Requirements</h3> β’ Hands-on experience in generative AI research and/or engineering, whether in industry or through academic work during the Bachelorβs / Masterβs / PhD degree with corresponding published work
β’ Demonstrated expertise in deep learning and transformer models
β’ Mastery of Python (PyTorch, numpy, agentic frameworks) for building AI workflows, fine-tuning models, and writing evaluations
β’ Strong foundation in data structures, algorithms, and software engineering principles
β’ Familiarity with methods for training LLMs (distillation, supervised fine-tuning, policy optimization)
β’ Excellent problem-solving and analytical skills, with a proactive approach to challenges <h3>ποΈ Benefits</h3> β’ Competitive salary
β’ Flexible PTO and WFH policy
β’ Top-of-the-line engineers and technology
β’ Opportunity to shape the direction of a pioneering open AI platform