Data Science & Machine Learning Engineer (m/f/d)

beON consult; Deutschland; On-site; USD 77,224 - 100,985; Full time

Benefits offered by this job

Performance-based bonus

Advancement opportunities

Collaborative work culture

Job summary

A leading IT consulting firm is seeking a Data Science & Machine Learning Engineer to develop real-world AI solutions. This position requires 3+ years of experience in deploying ML models, strong Python skills, and familiarity with BI tools and cloud platforms. The role is hybrid, based in Germany, and involves collaboration with multiple teams to ensure scalable integration of models. A competitive salary and advancement opportunities are included.

Qualifications

• 3+ years of hands‑on experience developing and deploying ML models in production environments.
• Strong Python skills and experience with ML frameworks (e.g., scikit‑learn, TensorFlow, PyTorch).
• Familiarity with Explainable AI (XAI) and ethical AI principles.

Responsibilities

• Design and optimize ML models for forecasting and anomaly detection.
• Develop and maintain robust ML pipelines for deployment and monitoring.
• Collaborate with data engineers and architects for scalable integration.

Skills

Python

Machine Learning frameworks

Data preprocessing

SQL

Communication skills

Tools

Power BI

AWS

Azure

GCP

Job description

About BeON

beON is a leading IT consulting firm based in Germany, delivering state‑of‑the‑art IT services and high‑performance software solutions to enterprise clients. We specialize in end‑to‑end digital transformation, AI system design, IT security, and advanced hybrid cloud architectures. With headquarters in Kiel and Düsseldorf and offices in Munich, Berlin, Frankfurt, Hamburg, Vienna, Lisbon, and Hyderabad (India), we foster a modern, collaborative, and agile work culture.

About The Role

As a Data Science & Machine Learning Engineer at beON, you will work on real‑world industrial and enterprise use cases — from modeling sensor and process data to deploying AI models in live environments. Your role will contribute to building intelligent systems that optimize processes, improve quality, and drive efficiency. We welcome applicants from diverse data science backgrounds who are eager to apply their skills in impactful, production‑ready solutions.

Job Details

• Work Location: and/or , Hybrid, Düsseldorf, Deutschland
• Employment type: Permanent, Full‑time
• Start: As soon as possible
• Language Requirements: English (German is a plus)
• Compensation: Competitive salary with performance‑based bonus and advancement opportunities

Your Responsibilities

• Design and optimize ML models for time series forecasting, anomaly detection, and computer vision (e.g., quality inspection)
• Apply advanced techniques such as LSTM, CNN, XGBoost, PCA, clustering, and Explainable AI (e.g., SHAP, LIME)
• Analyze structured and unstructured data from operational and sensor systems
• Develop and maintain robust ML pipelines for training, validation, deployment, and monitoring
• Collaborate with data engineers, solution architects, and IoT/Edge teams to ensure scalable integration
• Use SQL and BI tools (e.g., Power BI) to prepare and visualize large datasets
• Work with cloud platforms (e.g., AWS, Azure, GCP) for model deployment and MLOps lifecycle management

Your Profile

• 3+ years of hands‑on experience developing and deploying ML models in production environments
• Strong Python skills and experience with ML frameworks (e.g., scikit‑learn, TensorFlow, PyTorch)
• Proficient in data preprocessing, feature engineering, and model validation techniques
• Familiarity with Explainable AI (XAI), data governance, and ethical AI principles
• Solid SQL skills and experience with BI/dashboard tools such as Power BI
• Experience working with cloud‑based ML services (e.g., SageMaker, Azure ML, Vertex AI)
• Strong communication skills and ability to explain technical results to both technical and business stakeholders

Preferred Qualifications

• Experience in Industry 4.0, manufacturing, or process automation projects
• Familiarity with real‑time/streaming data platforms, time series databases, and tools like Grafana
• Understanding of MLOps pipelines and tools for automated model management and deployment
• Experience with orchestration tools such as Apache Airflow or dbt

Application Process

Ready to take the next step in your career with beON? Send your CV to [e-mail] with the subject line “Data Science & ML Engineer.” We respect your time — no cover letter required.