AI/ML Engineer: Generative AI, NLP & MLOps

Ethereum Technologies; Austin (TX); On-site; USD 110,000 - 170,000; Full time

Job summary

Ethereum Technologies is seeking an experienced AI/ML Engineer to design, develop, and deploy intelligent applications solving complex business problems. The role focuses on machine learning model development, data preprocessing, and integrating AI solutions into enterprise systems.

You will work with Python, SQL, NLP, and generative AI technologies, collaborating with data engineers and software developers to build scalable AI workflows and monitor model performance for continuous improvement.

Qualifications

• Experience designing and deploying ML models.
• Strong Python, SQL, and ML background.
• Experience with NLP and generative AI.

Responsibilities

• Design, develop, and implement machine learning models and AI-based solutions.
• Collect, clean, preprocess, and analyze datasets.
• Build predictive models using supervised and unsupervised learning.
• Develop and optimize ML algorithms for business applications.
• Work with NLP, deep learning, and generative AI technologies.
• Integrate ML models into enterprise applications.
• Collaborate with data engineers and software developers to build scalable AI solutions.
• Monitor model performance and implement improvements.
• Develop automated ML pipelines and workflows.
• Document model architecture, development processes, and results.

Skills

Python

SQL

Machine Learning

TensorFlow

PyTorch

Scikit-learn

NLP

Generative AI

LLMs

Prompt Engineering

Data Processing

Feature Engineering

MLOps

Statistical Analysis

Predictive Modeling

Job description

Ethereum Technologies is seeking an experienced AI/ML Engineer to design, develop, and deploy intelligent applications solving complex business problems. The role focuses on machine learning model development, data preprocessing, and integrating AI solutions into enterprise systems.

You will work with Python, SQL, NLP, and generative AI technologies, collaborating with data engineers and software developers to build scalable AI workflows and monitor model performance for continuous improvement.