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Vatic Labs in New York offers a challenging AI Researcher role focused on developing AI-driven quantitative trading strategies. You will explore market and alternative data, applying state-of-the-art models inspired by LLMs and deep neural networks.
Our team values collaboration, mentorship, and open exchange of ideas, with opportunities to publish and impact trading tech. Expect a rigorous research environment and strong growth.
As an AI Researcher at Vatic Labs, you will research and develop innovative AI-driven quantitative trading strategies. You will explore vast amounts of market and alternative data, inventing and applying a new generation of state-of-the-art technologies that are inspired by large language models, deep neural networks, transformers, and advanced prompt engineering methods (e.g. GPT-4) to discover and capitalize on trading opportunities.
The nature of the problems we work on is challenging, hence we hire some of the world's top AI talent to develop novel AI methods and trading strategies. Our team of talented researchers and technologists has been recognized as leaders in their field. Our distinguished researchers have been widely cited for their publications in top-tier, peer-reviewed scientific journals. We are passionate about hiring the best and the brightest, empowering them with the tools and mentorship needed to be successful. Our environment is highly collaborative and open, sharing AI and trading expertise across team members and fostering innovation and growth.
If You Possess All Or Most Of The Following, We Would Love To Explore What Is Available For You With Our Team
At Vatic, we’re serious about our work—but we also believe in balance, growth, and having fun along the way. Here’s what you can expect:
The base salary range for this role is between $175,000 and $250,000. The base salary range does not include any other form of compensation, such as any bonus amounts, or any benefits. Factors that may impact the agreed upon base salary within the range for a particular candidate include years of experience, level of education obtained, skill set, and other factors.