ML Engineer: Build & Deploy Data-Driven AI Solutions

EventMakers Entertainment; Atlanta (GA); On-site; USD 122,000 - 146,000; Full time

Job summary

EventMakers Entertainment in Atlanta is seeking a Machine Learning Engineer to design and implement innovative ML algorithms and models. You will work with cross-functional teams to analyze data, build predictive models, and deploy them into production environments.

The role requires a Bachelor's or Master's in CS/Math, practical ML experience, and proficiency with Python or R, and visualization tools; TensorFlow or PyTorch familiarity is a plus.

Qualifications

• Bachelor's or Master's degree in Computer Science, Mathematics, or related field.
• Proven experience as a Machine Learning Engineer or Data Scientist.
• Strong understanding of ML techniques (regression, classification, clustering, neural nets).
• Experience with large datasets using Python or R.
• Knowledge of data visualization tools (Tableau or Power BI).
• Familiarity with TensorFlow or PyTorch is a plus.
• Excellent problem-solving and attention to detail.
• Ability to work independently or in a team.

Responsibilities

• Develop and implement efficient ML algorithms and models.
• Work with large datasets to identify trends and insights.
• Collaborate with cross-functional teams to gather requirements.
• Deploy ML models into production environments.
• Evaluate and improve existing ML systems.
• Stay up to date with ML advancements.

Skills

Python

R

Deep learning

Problem-solving

Teamwork

Education

Bachelor's or Master's in CS/Math

Tools

Tableau

Power BI

TensorFlow

PyTorch

Job description

EventMakers Entertainment in Atlanta is seeking a Machine Learning Engineer to design and implement innovative ML algorithms and models. You will work with cross-functional teams to analyze data, build predictive models, and deploy them into production environments.

The role requires a Bachelor's or Master's in CS/Math, practical ML experience, and proficiency with Python or R, and visualization tools; TensorFlow or PyTorch familiarity is a plus.