Remote ML Engineer: Build Production-Ready Models

JobCenter; Horsens; Hybrid; DKK 67,000 - 90,000; Full time

Job summary

JobCenter in Horsens, Denmark, is seeking a Machine Learning Engineer to develop and implement algorithms and models that enable our company to make data-driven decisions. You will work closely with data scientists and software engineers to design, build and deploy ML solutions.

This role involves developing ML algorithms to solve complex business problems, collaborating to identify data sources and features, and integrating models into production systems.

Qualifications

• Bachelor's or Master's in Computer Science, Mathematics, or related field.
• 2+ years of experience developing machine learning solutions.
• Proficient in Python or Java.
• Strong understanding of regression, classification, clustering, etc.
• Experience with TensorFlow or PyTorch is a plus.
• Familiarity with AWS or Azure is preferred.
• Excellent problem-solving skills and attention to detail.

Responsibilities

• Develop and implement ML algorithms and models to solve complex business problems.
• Collaborate with data scientists to identify relevant data sources and features for model training.
• Work with software engineers to integrate machine learning models into production systems.
• Design experiments to evaluate model performance and make necessary improvements.
• Keep up-to-date with the latest developments in the field of machine learning and apply them to improve our systems.

Skills

Python/Java

ML algorithms

Model evaluation

Cloud platforms

Education

Bachelor's or Master's in CS/Math

Tools

TensorFlow

PyTorch

AWS

Azure

Job description

JobCenter in Horsens, Denmark, is seeking a Machine Learning Engineer to develop and implement algorithms and models that enable our company to make data-driven decisions. You will work closely with data scientists and software engineers to design, build and deploy ML solutions.

This role involves developing ML algorithms to solve complex business problems, collaborating to identify data sources and features, and integrating models into production systems.