Research Scientist (San Francisco)
Note: We have a preference for candidates that are able to work out of NYC or SF for this role!
About Patronus AI
Patronus AIs mission is to provide the security and risk management layer for AI. We are solving the problem of scalable oversight - how can humans continue to supervise AI systems when AI far outperforms them in many real world scenarios? Our vision is a world in which AI evaluates AI.Our founding team comes from top applied ML and research backgrounds, including Facebook AI Research (FAIR), Airbnb, Meta Reality Labs, and quant finance. As a team, we have published research papers at top ML conferences (NeurIPS, EMNLP, ACL), designed and launched Airbnbs first conversational AI assistant, pioneered causal inference at Meta Reality Labs, exited a quant hedge fund backed by Mark Cuban, and scaled 01 products at high growth startups. We are backed by Lightspeed Venture Partners and high profile operators like Amjad Masad, Gokul Rajaram, and Fortune 500 executives and board members. We are advised by Douwe Kiela, Adjunct Professor at Stanford University and former Head of Research at HuggingFace.
- Competitive salary and equity packages
- Health, dental, and vision insurance plans
- 401(k) plan
- Unlimited PTO
- Fun global offsites!
Responsibilities
As a Research Scientist at Patronus AI, you will be pivotal to solving the most important and challenging open research problems facing societys adoption of AI today, surrounding AI evaluation, language model understanding and robustness challenges.
In this role, you will:
- Develop state-of-the-art systems for AI evaluation. Implement algorithms and models based on state-of-the-art NLP advancements, especially in the areas of evaluation and LLM alignment.
- Conduct novel research on redteaming language models, automated evaluation and alignment.
- Scope out and lead research projects, including experiment design, timelines for research deliverables, understanding results.
- Develop processes for high quality research, including dataset collection, model training, benchmarking and inference.
- Experiment with latest technologies and proactively suggest experiments and improvements to research and ML systems. Adapt to changes in generative AI landscape, and incorporate new models into the platform when applicable.
- Assist in the construction of high quality, novel datasets for classification and generative tasks, through synthetic data augmentation techniques and publicly available datasets.
- Contribute to research to production efforts that advance product offerings.
- Collaborate closely with product and engineering in our globally-based team.
Qualifications
The number one qualification to succeed in this machine learning course is gumption - John Lafferty, CS Professor at Yale
Above all, we look for a proactive mindset, willingness to learn, relentless drive, and passion for working hands-on with customers. You are a great fit if you have a background in the following:
- Publications at leading AI conferences, journals or workshops, such as NeurIPS, ICML, EMNLP, ACL, AAAI.
- Experience conducting empirical NLP research in an academic or industry research lab.
- Knowledge and understanding of state-of-the-art machine learning concepts, with a focus on NLP. Familiarity with transformer-based architectures, attention mechanisms, evaluation metrics and benchmarks.
- Experience training language models in applied or research settings.
- Experience working and communicating cross functionally in a team environment.
- Creativity in problem solving and strong communication skills.
- Have good character, integrity and respect for others.
Patronus AI is an equal opportunity employer. We celebrate diversity in our workplace, and all qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or other legally protected characteristics.
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