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Crossing Hurdles

Machine Learning Engineer

Crossing Hurdles

Remote · Vertrag

Bewerben Sie sich als Erste/r!

Erfahrung
Beliebig
Gehalt
USD 30 – USD 160 / hour
Stellenangebote
1
Veröffentlicht
vor 3 Stunden
Work mode
Arbeiten von zu Hause
Eligibility
Professionals who can work remotely for 10 to 40 hours per week on a contract basis and are comfortable working from the United Kingdom.
Resume
Required to apply

Stellenbeschreibung

Role overview

This contract opportunity is for a Machine Learning Engineer working remotely from the United Kingdom. The role is structured around 10 to 40 hours per week and offers pay in the range of $30 to $160 per hour.

What you will do

  • Build, train, and put machine learning models into production using TensorFlow and Scikit-Learn to address practical business needs.
  • Prepare data for modeling by cleaning, transforming, and creating useful features from raw inputs.
  • Work closely with data scientists, data engineers, and business analysts to convert business requirements into scalable ML solutions.
  • Track model performance over time, assess results, and improve accuracy, reliability, and efficiency in live environments.
  • Keep clear records of the model development process and explain technical findings to both technical and non-technical stakeholders.
  • Keep pace with new machine learning research and techniques, applying relevant improvements to strengthen outcomes.

What we are looking for

  • Advanced hands-on experience with TensorFlow and Scikit-Learn across the full model lifecycle, from development to deployment.
  • Strong capability in data preprocessing, including missing-value treatment, outlier handling, and feature selection.
  • Proven experience building machine learning systems that are suitable for production use.
  • Good understanding of model choice, evaluation metrics, and tuning methods to improve results.
  • Ability to work autonomously in a remote setup and deliver consistently in a fast-moving, deadline-oriented environment.

Application process

Applicants are expected to go through an easy-apply step, monitor their email for follow-up communication, and complete resume review and interview stages.

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