Crypto Data Scientist / Machine Learning – LLM Engineer (Global – Remote – Non.US)

NLP PEOPLE; Oregon City (OR); Remote; USD 80,000 - 130,000; Full time

Job summary

An innovative company is seeking a skilled machine learning engineer to enhance their predictive models and AI capabilities. In this role, you will consult with management to define objectives, design machine learning systems, and solve complex data challenges. Your expertise in Python, Java, and R, along with a solid understanding of ML frameworks, will be critical in optimizing processes and ensuring accurate user recommendations. Join a forward-thinking team dedicated to leveraging AI for impactful solutions in the crypto investment space, where your contributions will drive significant advancements in technology and client satisfaction.

Qualifications

• 2+ years of experience as a machine learning engineer.
• Advanced proficiency with Python, Java, and R.

Responsibilities

• Consult with the manager to refine machine learning objectives.
• Design ML systems and self-running AI to automate predictive models.

Skills

Python

Java

R

Machine Learning Frameworks

Statistical Analysis

Problem-Solving

Data Modeling

Communication Skills

Time Management

Collaboration Skills

Education

Bachelor’s degree in Computer Science

Master’s degree in Data Science

Tools

ML Libraries

Data Structures

Software Architecture

Job description

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.
• Experience with crypto or web3 projects

About Token Metrics

Token Metrics helps crypto investors build profitable portfolios using artificial intelligence based crypto indices, rankings, and price predictions.

Token Metrics has a diverse set of customers, from retail investors and traders to crypto fund managers, in more than 50 countries.

PI270240547

Company:

Token Metrics

Qualifications:

Language requirements:

Specific requirements:

Educational level:

Level of experience (years):

Senior (5+ years of experience)

Tagged as: Computational Linguistics, Industry, Machine Learning, NLP, United States