Machine Learning Engineer, Entry Level

Emonics LLC; New York (NY); On-site; USD 95,000 - 120,000; Full time

Job summary

A technology solutions company based in New York seeks a Machine Learning Engineer to design, build, and deploy machine learning solutions. The ideal candidate will have a degree in a relevant field and strong skills in Python and data handling. Responsibilities include developing and training ML models, building data preprocessing workflows, and collaborating with engineering teams to ensure the reliability of ML systems. This position offers an opportunity to work in a collaborative environment focusing on operationalizing ML solutions.

Qualifications

• Degree in a relevant field like Computer Science or Data Science.
• Strong understanding of machine learning fundamentals and Python.
• Familiarity with data handling libraries such as pandas.
• Basic understanding of software engineering best practices like version control.

Responsibilities

• Develop and train ML models with reproducible pipelines.
• Build data preprocessing workflows and generate features.
• Deploy models to production and monitor their performance.
• Collaborate with stakeholders to define success metrics.

Skills

Strong Python

Data handling (pandas)

ML fundamentals

Understanding of Git

Education

Degree in CS, Data Science, Engineering, or related field

Tools

scikit-learn

Docker

Airflow

Job description

We are hiring a Machine Learning Engineer to help design, build, and deploy ML solutions. This role focuses on turning models into reliable systems and collaborating with engineering teams to operationalize ML.

What you will do

• Develop and train ML models with reproducible pipelines
• Build data preprocessing workflows and feature generation
• Deploy models to production and monitor performance
• Work with stakeholders to define success metrics and test outcomes
• Document experiments and contribute to best practices

What you are looking for

• Degree in CS, Data Science, Engineering, or related field
• Strong Python, data handling (pandas), and ML fundamentals
• Familiarity with scikit-learn and basic model evaluation
• Understanding of software engineering basics (Git, testing, modular code)

Nice to have

• Experience with ML pipelines, Airflow, or workflow orchestration
• Exposure to CI/CD, Docker, and cloud services