Machine Learning Engineer

On-siteMidML Engineerposted 5d ago

✦Role summaryAI-generated

This role focuses on bridging ML research with production systems, requiring hands-on experience in deploying scalable models while collaborating with cross-functional teams to solve real-world business challenges in a fast-paced gaming environment. The candidate will optimize model performance end-to-end, from data pipelines to monitoring, ensuring seamless integration into Betsson Group’s core products.

Skills required

Python Model deployment Mlops pipelines Feature engineering Distributed training Model monitoring Api integration Data preprocessing Machine learning MLflow Spark Cloud computing AWS GCP Azure

About this role

The Wow

As a Machine Learning Engineer, you will play a pivotal role in designing, developing, and deploying advanced machine learning models that enhance our products and services. You will collaborate with cross-functional teams to solve complex problems and drive the adoption of machine learning solutions across the organization.

A taster of what you will be involved with:

Design, implement, and optimize machine learning models to solve complex business problems.
Oversee the entire machine learning lifecycle, from data collection and pre-processing to model deployment and monitoring.
Work closely with data scientists, software engineers, and product managers to integrate machine learning models into production systems.
Stay up-to-date with the latest advancements in machine learning and apply them to improve model performance and functionality.
Write and maintain high-quality, production-ready code for machine learning models and services.
Provide guidance and mentorship to junior team members, fostering a culture of continuous learning and improvement.

What we are looking for:

Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
3-5 years of experience as a Machine Learning Engineer, with a strong track record of deploying models in production environments.
Proficiency in Python, MLFlow and Spark would be considered an asset.
Experience with cloud platforms (AWS, GCP, Azure). Experience with AWS Sagemaker would be preferred.
Strong problem-solving skills and the ability to analyse complex data sets to derive actionable insights.
Excellent communication skills, with the ability to explain complex concepts to both technical and non-technical stakeholders.