ML Engineer - Flexible Hours, Relocation Help

Jing Hau; Roskilde; On-site; DKK 88,000 - 106,000; Full time

Benefits offered by this job

Relocation assistance

Visa sponsorship

Flight ticket reimbursement

Flexible working hours

Career development opportunities

Job summary

Jing Hau in Roskilde, Denmark is seeking a skilled Machine Learning Engineer to design, implement and maintain ML models and algorithms. You will analyze large datasets and collaborate with data scientists and software engineers to deliver scalable solutions.

The role involves experimenting with different techniques, optimizing models for performance, and communicating complex ideas to non-technical stakeholders.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science or related field.
• Minimum of 3 years of experience as a Machine Learning Engineer or similar role.
• Strong knowledge of ML algorithms such as regression, classification, clustering, etc.
• Proficiency in Python, Java or C++ and ML frameworks.

Responsibilities

• Design, implement and maintain machine learning models and algorithms.
• Collaborate with data scientists to develop efficient data processing pipelines.
• Optimize machine learning models for performance and scalability.
• Conduct experiments to evaluate approaches.
• Communicate complex technical concepts to non-technical stakeholders.
• Stay up-to-date with latest ML techniques and tools.

Skills

ML algorithms

Python

Java

C++

TensorFlow

PyTorch

Hadoop

Spark

Hive

Problem solving

Communication

Education

Bachelor's or Master's degree in Computer Science or Data Science

Tools

Python

Java

C++

TensorFlow

PyTorch

Hadoop

Spark

Hive

Job description

Jing Hau in Roskilde, Denmark is seeking a skilled Machine Learning Engineer to design, implement and maintain ML models and algorithms. You will analyze large datasets and collaborate with data scientists and software engineers to deliver scalable solutions.

The role involves experimenting with different techniques, optimizing models for performance, and communicating complex ideas to non-technical stakeholders.