ML Engineer: Scale Real-World AI in NYC & Growth

Onyx National Solutions; New York (NY); On-site; USD 120,000 - 170,000; Full time

Job summary

Onyx National Solutions, a New York City tech firm, seeks a Machine Learning Engineer for a full-time role. You will design, deploy, and maintain ML models to tackle real-world business problems, collaborating with cross-functional teams across the organization.

The role emphasizes data preprocessing, feature engineering, model evaluation, and staying current with ML advances. Strong communication and teamwork are essential for success in a fast-paced environment.

Qualifications

• Bachelor's degree in Computer Science, Mathematics, Statistics, or related field.
• 2+ years of experience in machine learning or data science.
• Strong programming skills in Python, R, or a similar language.
• Experience with TensorFlow, PyTorch, or scikit-learn.
• Knowledge of data preprocessing, feature engineering, and model evaluation techniques.
• Familiarity with AWS, GCP, or Azure is a plus.
• Excellent communication and teamwork in a fast-paced, collaborative environment.

Responsibilities

• Design, develop, and deploy machine learning models to solve real-world problems.
• Collaborate with cross-functional teams to translate business needs into technical solutions.
• Optimize and scale ML systems to meet performance and scalability requirements.
• Stay up-to-date with latest ML and data science developments and apply them to projects.
• Document work and share insights to foster continuous learning and improvement.

Skills

Python

R

Data preprocessing

Feature engineering

Model evaluation

Communication & teamwork

Cloud basics

Education

Master's degree in Computer Science/Data Science or related field

Bachelor's degree in CS/Math/Stats or related field

Tools

TensorFlow

PyTorch

scikit-learn

AWS

GCP

Azure

Job description

Onyx National Solutions, a New York City tech firm, seeks a Machine Learning Engineer for a full-time role. You will design, deploy, and maintain ML models to tackle real-world business problems, collaborating with cross-functional teams across the organization.

The role emphasizes data preprocessing, feature engineering, model evaluation, and staying current with ML advances. Strong communication and teamwork are essential for success in a fast-paced environment.