Machine Learning Engineer

PPOAR; Roskilde; On-site; DKK 84,902 - 101,695; Full time

Benefits offered by this job

Accommodation

Visa support

Travel arrangements

Job summary

PPOAR is hiring a Machine Learning Engineer to join our team in Roskilde. The candidate will develop and implement machine learning algorithms and models to support our business goals while collaborating with data scientists and software engineers for data analysis.

The ideal candidate will have a strong background in mathematics, statistics, and computer science but prior experience in machine learning is not required. A competitive salary of $1300 per month, accommodation, and support for visa and travel arrangements will be provided.

Qualifications

• Strong background in mathematics, statistics, and computer science.
• Experience with programming languages such as Python or R.
• A passion for machine learning; prior experience is not required.

Responsibilities

• Develop and implement machine learning algorithms and models to support our business objectives.
• Collaborate closely with data scientists and software engineers to collect, clean, and analyze data.
• Assist with deployment of machine learning models into production systems.

Job description

Machine Learning Engineer – Roskilde

We are hiring a Machine Learning Engineer to join our team in Roskilde.

Responsibilities

• Develop and implement machine learning algorithms and models to support our business objectives.
• Collaborate closely with data scientists and software engineers to collect, clean, and analyze data.
• Assist with deployment of machine learning models into production systems.

Qualifications

• Strong background in mathematics, statistics, and computer science.
• Experience with programming languages such as Python or R.
• A passion for machine learning; prior experience is not required.

Compensation & Benefits

A competitive salary of 1300$ per month, accommodation, and support for visa and travel arrangements.

EEO Statement

This position is open to all genders and nationalities.