Machine Learning Engineer

At Sentient, we’re pioneering the open artificial general intelligence (AGI) frontier, enabling loyalty and monetization of open-source models through cutting-edge research. Our platform is designed to democratize AI development, empowering communities to collaboratively train, control, monetize, and build on top of AI models in a truly open and accessible ecosystem, ensuring fair value distribution to AI builders.

Sentient is backed by leading Silicon Valley venture capital firms including Founders’ Fund and founded by top AI academics and protocol founders.

Job Summary

We're seeking an exceptional ML Engineer to join our team in building Sentient Chat, a multi-agent product aiming to compete with leading consumer AI competitors. This role is a unique opportunity to work on end-to-end AI system development, from data analysis to executing on tangible AI feature improvements. The ideal candidate will have a strong focus on data analysis, natural language processing, and understanding of consumer AI performance expectations.

Responsibilities

• Build data pipelines for natural language processing from Sentient Chat logs, analyze feedback, and extract product-level insights
• Run public and private benchmarks on internal AI sub-systems to assess performance across prototypes and competing products
• Own and compile custom datasets to define acceptance criteria throughout the product development lifecycle
• Conduct basic market research to suggest ways to improve AI performance on target metrics
• Organize scripts and data to present concrete AI failure cases and identify improvement areas
  
  

Required Qualifications

• Experience in AI/ML: 2+ years of hands-on experience in data analysis, machine learning, or a related field, with a focus on natural language processing (NLP) and/or generative AI.
• Technical Skills: Strong proficiency in Python, with experience in libraries such as PyTorch, NumPy, and pandas.
• Data Analysis: Proven ability to collect, analyze, and interpret large datasets, with experience in data profiling and evaluation.
• Problem-Solving: Excellent problem-solving and analytical skills, with a proactive approach to challenges and a strong foundation in data science. Ability to derive and answer product-level questions to improve the end-consumer experience.
  
  

All successful candidates will be contacted within 72 hours.