2 Data & Machine Learning Engineers ( 1 Senior & 1 Mid-level/Junior)

emagine is currently looking for two Data & Machine Learning Engineers (Senior and Mid-level) for a global technology client based in Stockholm.

Start Date: 2026-09-01

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

Location: Stockholm, Sweden (Hybrid)

Assignment Overview

Our client is undertaking a strategic initiative to strengthen its data-driven decision-making capabilities within a large-scale, high-volume messaging and communications environment. The consultants will play a key role in building and enhancing data pipelines, real-time analytics capabilities, machine learning foundations, and intelligent routing and pricing systems.

The assignment will be delivered within a modern cloud-native architecture built around Go microservices, Kafka-based event streaming, ClickHouse data platforms, Kubernetes, and machine learning-enabled services.

We are looking for one Senior Data & Machine Learning Engineer and one Mid-Level Data & Machine Learning Engineer.

Must-Have Requirements (non-negotiable)

Technical Skills

• Strong Data Engineering background with software development experience, preferably in Go (Golang)
• Experience working with databases, ideally ClickHouse
• Experience with Kubernetes and application deployment

Personal Qualities

• Strong communication and collaboration skills
• Proactive problem solver
• Curious and eager to learn
• Team-oriented and supportive of colleagues

Highly Meritorious

• Experience within telecommunications, messaging, routing, billing, or CPaaS environments
• Experience with Machine Learning Engineering and production deployment of ML models

Senior Data & Machine Learning Engineer

About The Assignment

We are seeking an experienced Senior Data & Machine Learning Engineer to design and develop intelligent data products and predictive capabilities supporting mission-critical messaging services.

You will work within a large-scale data ecosystem and be responsible for creating data foundations, scoring mechanisms, forecasting models, anomaly detection capabilities, and machine learning pipelines that enable automation and business optimization.

This role requires a combination of strong software engineering, data engineering, and machine learning expertise.

Responsibilities

Pricing Intelligence & Forecasting

• Develop simulation models and forecasting capabilities
• Build cost and margin prediction models
• Deliver pricing recommendations based on authoritative business data

Dynamic Route Scoring

• Create scoring models using real-time and historical datasets
• Continuously evaluate route quality and performance metrics
• Support automated routing decision engines

Real-Time Anomaly Detection

• Build highly responsive detection models
• Identify service degradations, network anomalies, and operational issues in near real time
• Enable automated reactions and alerts

Data Architecture

• Design scalable and AI-ready ClickHouse data models
• Ensure data consistency, modularity, and quality standards
• Support future analytics and machine learning initiatives

Production Engineering

• Develop and integrate solutions within a Go-based microservices ecosystem
• Deploy and maintain machine learning inference services
• Ensure high performance and low-latency operation in streaming environments

Required Experience

Programming

• Strong experience with Go (Golang)
• Strong experience with Python

Data & Infrastructure

• ClickHouse or similar analytical databases
• Apache Kafka
• Protobuf
• Redis
• Kubernetes
• Helm
• Grafana
• Prometheus

Machine Learning

• Dynamic scoring models
• Forecasting and simulation models
• Real-time anomaly detection
• Streaming inference architectures
• MLOps and production deployment
• Feature engineering and data preparation

Preferred Experience

• Telecommunications
• Messaging platforms
• Routing optimization
• Billing systems
• Pricing engines

Mid-Level Data & Machine Learning Engineer

About The Assignment

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.

Responsibilities

Data Pipeline Development

• Build and maintain Go-based Kafka ingestion pipelines
• Process both real-time and aggregated data streams
• Ensure scalability, reliability, and data quality

Data Preparation & Structuring

• Clean, normalize, and structure data
• Create AI-ready datasets and ClickHouse tables
• Support downstream analytics and machine learning workloads

Microservices Development

• Develop APIs and supporting backend services
• Expose aggregated metrics and data products internally
• Contribute to platform scalability and reliability

ML Platform Support

• Prepare data features for machine learning workflows
• Support deployment and monitoring of ML solutions
• Collaborate closely with senior engineers and architects

Monitoring & Reliability

• Implement observability and monitoring solutions
• Utilize Prometheus and Grafana
• Ensure stable and reliable production systems

Required Experience

Programming

• Good proficiency in Go (Golang)
• Experience with Python

Data & Infrastructure

• SQL
• Analytical databases (ClickHouse experience is highly desirable)
• Kafka or similar messaging systems
• Protobuf
• Docker
• Kubernetes
• Grafana
• Prometheus

Desired Mindset

• Strong interest in data engineering and machine learning
• Understanding of feature engineering and data preparation
• Desire to learn MLOps and production ML deployments
• Strong analytical and problem-solving skills

Preferred Experience

• Telecommunications data
• Routing systems
• Billing records
• Messaging platforms