Junior/Mid-Level Data & Machine Learning engineer

emagine is currently looking for a Junior or Mid- level ML and Data Engineer for a global technology client based in Stockholm.

Start Date: ASAP

End Date: 2027-08-31 (extension possible)

Location: Sweden, remote

Assignment Overview

We are looking for an ambitious Data & Machine Learning Engineer who will help build and maintain the data infrastructure powering advanced analytics and machine learning initiatives.

Working closely with senior technical specialists, you will focus on developing data ingestion pipelines, preparing high-quality datasets, building microservices, and supporting production machine learning workflows.

This is an excellent opportunity for someone who wants to deepen their expertise in data engineering, distributed systems, and MLOps.

Data Pipeline Development

Build and maintain Go-based Kafka ingestion pipelinesProcess both real-time and aggregated data streamsEnsure scalability, reliability, and data quality

Data Preparation & Structuring

Clean, normalize, and structure dataCreate AI-ready datasets and ClickHouse tablesSupport downstream analytics and machine learning workloads

Microservices Development

Develop APIs and supporting backend servicesExpose aggregated metrics and data products internallyContribute to platform scalability and reliability

ML Platform Support

Prepare data features for machine learning workflowsSupport deployment and monitoring of ML solutionsCollaborate closely with senior engineers and architects

Monitoring & Reliability

Implement observability and monitoring solutionsUtilize Prometheus and GrafanaEnsure stable and reliable production systems

Required Experience

Programming

Good proficiency in Go (Golang)Experience with Python

Data & Infrastructure

SQLAnalytical databases (ClickHouse experience is highly desirable)Kafka or similar messaging systemsProtobufDockerKubernetesGrafanaPrometheus

Desired Mindset

Strong interest in data engineering and machine learningUnderstanding of feature engineering and data preparationDesire to learn MLOps and production ML deploymentsStrong analytical and problem-solving skills