Job Description

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
  
  

• 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
• Familiarity with methods for training LLMs (distillation, supervised fine-tuning, policy optimization)
• Excellent problem-solving and analytical skills, with a proactive approach to challenges

Skills Required

• Strong Communication skills