LLM Data Researcher
Turing- Full Time
- Junior (1 to 2 years)
Token Metrics
Candidates should possess a Bachelor's degree in computer science, data science, mathematics, or a related field, and preferably a Master’s degree in computational linguistics, data science, data analytics, or a similar discipline. They must have at least two years of experience as a machine learning engineer, along with advanced proficiency in Python, Java, and R code, and extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture. Furthermore, candidates should demonstrate in-depth knowledge of mathematics, statistics, and algorithms, and experience with crypto or web3 projects.
The Machine Learning Engineer will consult with the manager to determine and refine machine learning objectives, design machine learning systems and self-running artificial intelligence (AI) to automate predictive models, transform data science prototypes and apply appropriate ML algorithms and tools, and ensure that algorithms generate accurate user recommendations. They will also solve complex problems with multi-layered data sets, as well as optimize existing machine learning libraries and frameworks, develop ML algorithms to analyze huge volumes of historical data to make predictions, stress test, perform statistical analysis, and interpret test results for all market conditions, document machine learning processes, and keep abreast of developments in machine learning.
Cryptocurrency investment platform using machine learning
Token Metrics is a cryptocurrency investment platform that uses machine learning to help users identify profitable investment opportunities and avoid scams. It offers services like cryptocurrency reviews, price predictions, and in-depth analysis, catering to both novice and experienced investors. The platform operates on a subscription model, providing access to premium features such as a private investor group and webinars. The goal of Token Metrics is to make crypto investing more accessible and less risky for its clients.