Token Metrics is searching for a highly capable machine learning engineer to optimize our machine learning systems. You will be evaluating existing machine learning (ML) processes, performing statistical analysis to resolve data set problems, and enhancing the accuracy of our AI software's predictive automation capabilities. As a machine learning engineer, you should demonstrate solid data science knowledge and experience. A first-class machine learning engineer will be someone whose expertise translates into the enhanced performance of predictive models.
Responsibilities
Consulting with the manager to determine and refine machine learning objectives.
Designing machine learning systems and self-running artificial intelligence (AI) to automate predictive models.
Transforming data science prototypes and applying appropriate ML algorithms and tools.
Ensuring that algorithms generate accurate user recommendations.
Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks.
Developing ML algorithms to analyze huge volumes of historical data to make predictions.
Stress testing, performing statistical analysis, and interpreting test results for all market conditions.
Documenting machine learning processes.
Keeping abreast of developments in machine learning.
Requirements
Bachelor's degree in computer science, data science, mathematics, or a related field.
Master’s degree in computational linguistics, data science, data analytics, or similar will be advantageous.
At least two years' experience as a machine learning engineer.
Advanced proficiency with Python, Java, and R code.
Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture.
LLM fine-tuning experience and working with LLM Observability
In-depth knowledge of mathematics, statistics, and algorithms.
Superb analytical and problem-solving abilities.
Great communication and collaboration skills.
Excellent time management and organizational abilities.
