Junior ML Engineer: Grow in Production ML & MLOps

Errgo; New York (NY); On-site; USD 85,000 - 110,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401(k)

Paid time off

Job summary

Errgo is seeking a Junior Machine Learning Engineer to contribute to building and deploying ML models across the platform, working with experienced engineers and data scientists, gaining hands-on experience through the full ML lifecycle—from data preparation to production deployment.

The role offers mentorship, exposure to production ML systems, and the opportunity to grow technical skills in MLOps while delivering impactful projects.

Qualifications

• 0-2 years of experience in machine learning or data science
• Strong Python skills with experience in ML libraries (PyTorch, TensorFlow, scikit-learn)
• Understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics)
• Familiarity with SQL and data manipulation (pandas, numpy)
• Exposure to cloud platforms (AWS, GCP) is a plus
• Bachelor's or Master's degree in Computer Science, Statistics, or related field

Responsibilities

• Assist in developing and training machine learning models using PyTorch or TensorFlow
• Write Python code for data preprocessing, feature engineering, and model evaluation
• Help build and maintain ML pipelines for training and inference
• Collaborate with data engineers to access and process training data
• Document model performance, experiments, and technical decisions
• Learn MLOps practices and contribute to model deployment workflows

Education

Bachelor's or Master's degree in Computer Science, Statistics, or related field

Tools

PyTorch

TensorFlow

scikit-learn

SQL

pandas

numpy

AWS

GCP

Job description

Errgo is seeking a Junior Machine Learning Engineer to contribute to building and deploying ML models across the platform, working with experienced engineers and data scientists, gaining hands-on experience through the full ML lifecycle—from data preparation to production deployment.

The role offers mentorship, exposure to production ML systems, and the opportunity to grow technical skills in MLOps while delivering impactful projects.