Senior Machine Learning Engineer - Databricks (m/f/*)

Ultra Tendency; Magdeburg; Hybrid; EUR 40.000 - 60.000; Vollzeit

Zusammenfassung

An international Data Engineering consultancy is looking for a Senior ML Engineer to design and implement scalable machine learning solutions on the Databricks Lakehouse Platform. The ideal candidate will have 3–5 years of experience, hands-on knowledge of Databricks and ML workflows, plus strong problem-solving skills. This position offers flexible work options, career acceleration, and opportunities to tackle unique projects within a supportive community.

Leistungen

Flexible work options

Paid certifications

Educational resources

Qualifikationen

• 3–5 years of experience in solution engineering or similar hands-on technical roles.
• Professional German & English communication skills (C1-level, written and spoken).
• Hands-on experience with Databricks on Azure, AWS, or GCP.

Aufgaben

• Design, develop, and maintain scalable machine learning pipelines on the Databricks Lakehouse Platform.
• Perform exploratory data analysis (EDA), data cleaning, and model evaluation.
• Collaborate with data engineers to translate real-world problems into ML solutions.

Kenntnisse

Databricks

Python

ML Engineering

Spark

Machine Learning

Tools

MLflow

Delta Lake

Git

Airflow

Jobbeschreibung

Our Engineering community is growing, and we’re now looking for a Senior ML Engineer - Databricks (m/f/*), to join our team in Germany, supporting our global growth.

As a Senior Machine Learning Engineer (m/f/*), you will lead the design and implementation of advanced data and AI solutions on the Databricks Lakehouse Platform. Your focus will lie in building robust ML pipelines, enabling GenAI capabilities, and delivering production‑grade solutions that support data‑driven innovation at scale.

WHAT WE OFFER

• Flexible work options, including fully remote or hybrid arrangements (candidates must be located in Germany)
• A chance to accelerate your career and work with outstanding colleagues in a supportive learning community split across 3 continents
• Contribute your ideas to our unique projects and make an impact by turning them into reality
• Balance your work and personal life through our workflow organization and decide yourself if you workat home, in the office, or on a hybrid setup
• Annual performance review, and regular feedback cycles, generating distinct value by connecting colleagues through networks rather than hierarchies
• Educational resources such as paid certifications, unlimited access to Udemy Business, etc.
• Local, virtual, and global team events, in which UT colleagues become acquainted with one another

WHAT YOU'LL DO

• Design, develop, and maintain scalable machine learning pipelines on the Databricks Lakehouse Platform using Spark, Delta Lake, and MLflow.
• Perform exploratory data analysis (EDA) , data cleaning, feature engineering, and model evaluation to support data-driven use cases.
• Collaborate with data engineers and business stakeholders to translate real‑world problems into ML solutions .
• Deploy models using MLflow, manage model versioning, and set up monitoring and retraining strategies.
• Optimize the performance and cost‑efficiency of ML workloads on Databricks clusters.
• Apply best practices in MLOps , ensuring reproducibility, governance, and scalability of ML solutions.
• Guide and mentor team members on Databricks, ML engineering best practices

WHAT YOU'LL BRING

• 3–5 years of experience in solution engineering or similar hands‑on technical roles.
• Hands‑on experience withDatabricks (on Azure, AWS, or GCP), especially Spark (PySpark or Scala), Delta Lake, and MLflow.
• Deep understanding of the machine learning lifecycle, including data prep, modeling, evaluation, and deployment.
• Proficiency in Python, with solid foundations in ML libraries (e.g., scikit‑learn, pandas).
• Experience building production‑ready ML pipelines and working with large‑scale datasets.
• Familiarity with orchestration tools (e.g., Databricks Workflows, Airflow) and version control (Git/GitHub).
• Strong problem‑solving and communication skills, with the ability to explain complex models and logic to stakeholders.
• Professional German & English communication skills (C1‑level, written and spoken).

NICE TO HAVE

• Experience with MLOps workflows: model monitoring, automated retraining, A/B testing.
• Exposure to cloud‑native architectures, CI/CD for ML, and infrastructure‑as‑code (e.g., Terraform).
• Knowledge of Databricks Unity Catalog for model governance and security.
• Experience working in regulated or enterprise data environments.

Did we pique your interest, or do you have any questions?

Ultra Tendency is an international premier Data Engineering consultancy forBig Data, Cloud, Streaming,IIoT andMicroservices. We design, build, and operate large‑scale data‑driven applications for major enterprises such as the European Central Bank, HUK‑Coburg, Deutsche Telekom, and Europe’s largest car manufacturer. Founded in Germany in 2010, UT has developed a reliable client base and now runs 8 branches in 7 countries across 3 continents.

We do more than just leverage tech, we build it. At Ultra Tendency we contribute source code to +20 open‑source projects includingAnsible, Terraform,NiFi, andKafka. Our impact on tech and business is there for anyone to see. Enterprises seek out Ultra Tendency because we solve the problems others cannot.

We love the challenge: together, we tackle diverse and unique projects you will find nowhere else. In our knowledge community, you will be a part of a supportive network, not a hierarchy. Constant learning and feedback are our drivers for stable development. With us you can develop your individual career through work‑life balance.

We evaluate your application based on your skills and corresponding business requirements. Ultra Tendency welcomes applications from qualified candidates regardless of race, ethnicity, national or social origin, disability, sex, sexual orientation, or age.

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