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About Sentient
At Sentient, we’re pioneering the decentralized artificial general intelligence (AGI) frontier, breaking free from the constraints of centralized AI models. Our cutting-edge platform is designed to democratize AI development, empowering communities to collaboratively train and control AI models in a truly open and accessible ecosystem.
Fueled by our expertise in distributed systems, cryptography, and AI, we’re building a game-changing environment that fosters open-source development and ensures fair value distribution. Say goodbye to the monopolies of the past – Sentient’s decentralized network promotes model composability and adherence to our foundational principles of transparency, trust, and inclusivity.
Imagine being part of a team that’s shaping the future of AGI, where innovation knows no boundaries, and the collective intelligence of global communities drives progress. Join us on this exhilarating journey as we redefine the AI landscape, unleashing the full potential of trustless, decentralized AGI.
Sentient is backed by leading Silicon Valley venture capital firms including Founders’ Fund, Pantera, and Framework.
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
Familiarity with methods for training LLMs (distillation, supervised fine-tuning, policy optimization)
Excellent problem-solving and analytical skills, with a proactive approach to challenges
Values
Appreciate and pursue deep expertise
Embrace extreme ownership and bias for action
Want to take risks and act upon ambition with integrity and empathy
Pursue relentless innovation and experimentation
Invest in personal growth and team collaboratio
Benefits
Competitive salary
Flexible PTO and WFH policy
Top-of-the-line engineers and technology
Opportunity to shape the direction of a pioneering open AI platform
