Why This Role Stands Out
Thrive at Vatic Labs as an AI Researcher by pushing the boundaries of quantitative trading strategies using cutting-edge AI and LLMs, with a competitive salary of $175,000 - $250,000. This role is perfect for PhD-level quantitative scientists eager to innovate within a highly collaborative environment and contribute to groundbreaking research. Apply today to join a team recognized for its leadership and passion for empowering top AI talent.
Quick Overview
Job Description
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:
- Earned or will earn a Ph.D. in a quantitative field, such as Computer Science, Electrical and Computer Engineering, Applied Math, Statistics, Quantitative Finance, Cognitive Science, Physics or another field of science.
- Experience analyzing large data sets with rigorous statistical and ML/AI approaches, including classification, clustering, regression (linear and nonlinear), optimization, signal processing, filtering and smoothing, time-series analysis, hidden Markov models, high-dimensional data analysis, vector quantization, decision tree methods, EM methods, Bayesian methods, variational inference methods, and neural networks.
- Demonstration of deep knowledge of large language models and deep neural networks for practical applications (e.g. NLP, vision, speech, signal processing, scientific computing, finance, etc). Finance applications preferred but not necessary.
- Ability to generate impactful research in academic or professional pursuits.
- Advanced understanding and experience of practical programming languages and software tools for data analysis and ML/AI applications, such as Python, C++, PyTorch, Tensorflow, etc.
- Interest and enthusiasm for learning about financial markets (previous experience not required).
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:
- Flat structure with direct executive exposure – Work closely with leadership and make an impact from day one.
- Comprehensive health benefits – Full health insurance coverage for employees and dependents.
- Daily meals provided – Enjoy free breakfast, lunch, and dinner at the office.
- Gym membership – Stay healthy with a gym reimbursement, in addition to our onsite gym.
- Unlimited office snacks – Fuel your day with your favorite snacks, always stocked.
- Fun team outings – Build camaraderie and unwind with regular events.
- Organized poker, ping pong, and game nights – We’re a competitive group that enjoys getting together to challenge one another.
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.
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