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AI Researcher

Remote:

Full Remote

Salary:

6 - 6K yearly

Experience:

Mid-level (2-5 years)

Work from:

United Kingdom

Offer summary

Qualifications:

3+ years in generative AI research/engineering, Expertise in deep learning and transformers, Mastery of Python (PyTorch, numpy), Strong foundation in algorithms.

Key responsabilities:

Conduct generative AI research
Design new agent architectures
Evaluate experiments on LLMs
Execute data engineering tasks
Integrate models with multi-modal capabilities
Replicate theoretical approaches and algorithms

Sentient Foundation Information Technology & Services Startup https://www.sentient.foundation

11 - 50 Employees

See more Sentient Foundation offers

Job description

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 on 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

3+ years hands-on experience in generative AI research and/or engineering, whether in industry or through academic work during the 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