Remote Machine Learning Engineer

Angenex; Jersey City (NJ); Remote; USD 90,000 - 120,000; Full time

Job summary

A leading data analytics company based in Jersey City is seeking a Remote Machine Learning Engineer to join their team. The role involves building and deploying ML pipelines and managing the MLOps infrastructure to optimize models. The ideal candidate should have over 1 year of experience in machine learning and proficiency in Python, along with a strong background in data manipulation and statistical analysis. This position offers the opportunity to work with cutting-edge technology in the analytics field.

Qualifications

• 1+ years of professional experience as a Machine Learning Engineer or production-focused Data Scientist.
• Proficiency across topics in machine learning and statistics.
• Fluency in Python coding and data manipulation (SQL, Spark, Pandas).

Responsibilities

• Build and deploy the ML pipelines that power the company machine learning platform.
• Manage MLOps infrastructure to monitor and optimize models.

Skills

Machine Learning

Python

Data Manipulation

Statistical Analysis

MLOps

Education

Advanced degree in computer science, mathematics, statistics or related area

Tools

AWS

Docker

Linux

Scikit-Learn

PyTorch

Keras

Tensorflow

Job description

About the job Remote Machine Learning Engineer

Job Description

We're seeking an outstanding ML Engineer to join our data team and help build out best-in-class machine learning solutions on our platform, powering innovative solutions in marketing & sales and commercial analytics.

Responsibilities

• Build and deploy the ML pipelines that power the company machine learning platform.
• Manage MLOps infrastructure to monitor and optimize models.

Qualifications

Experience

• 1+ years of professional experience as a Machine Learning Engineer or production-focused Data Scientist.
• Proficiency across topics in machine learning and statistics.
• Fluency in Python coding as well as data manipulation (SQL, Spark, Pandas)
• Broad familiarity with the Python ecosystem and common libraries including Scikit-Learn, XGBoost, PyTorch, Keras, Tensorflow, Pandas, and common ML cloud services.
• Familiarity with CNNs, RNN, LSTMs, and the latest research trends.
• Experience implementing, deploying, and maintaining production machine learning systems.
• Experience monitoring and optimizing model performance.
• Experience with Linux, Docker and AWS, and basic development operations.
• Advanced degree in computer science, mathematics, statistics or related area of study strongly preferred.