Remote Machine Learning Engineer

Angenex

$100K — $140K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 1+ years of experience as a Machine Learning Engineer or production-focused Data Scientist.
  • Proficient in machine learning concepts and statistical analysis.
  • Fluent in Python and skilled in data manipulation tools (SQL, Spark, Pandas).
  • Familiar with the Python ecosystem and major ML libraries (Scikit-Learn, XGBoost, PyTorch, Keras, Tensorflow).
  • Knowledgeable in CNNs, RNNs, LSTMs, and current trends in machine learning.
  • Skilled in deploying and maintaining production machine learning systems.
  • Proficient with Linux, Docker, AWS, and basic dev operations.

Responsibilities

  • Build and deploy machine learning pipelines for the company’s platform.
  • Manage MLOps infrastructure to ensure model performance and optimization.
  • Continuously monitor model performance metrics.
Full Job Description
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.

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