20 beste Stellen als machine learning engineer in berlin – aktuell auf Personalsuche

ML Ops Engineer
Zeta Global —Berlin
- Informatik
- Wartung
- Master
- Flexible Arbeitszeiten
10 Tage
Applied Scientist (f/m/d)
Siemens —Berlin
- Vollzeit
- Hybrides Arbeiten
- Informatik
- Forschungserfahrung
- Master
8 Std.
Biomarker Data Scientist (all gender)
Bayer —Berlin
- 77.300 € – 93.800 € pro Jahr
- Vollzeit
- Doktorat
- Informatik
- Master
10 Tage
Quereinsteiger Physiker / Mathematiker als Software Engineer Data & AI (mwd)
HMS Analytical Software GmbH —Berlin
- Teilzeit
- Hybrides Arbeiten
- Englisch
- Machine Learning
- Künstliche Intelligenz
- Erfolgsbeteiligung
- Flexible Arbeitszeiten
Data Scientist
adsquare GmbH —Berlin
- 60.000 € – 70.000 € pro Jahr
- Vollzeit
- Doktorat
- Forschungserfahrung
- Master
AI Engineer
Kuro Technology —Berlin
- 80.000 € – 120.000 € pro Jahr
- Vollzeit
- Azure
- Master
- AWS
Direkt bewerben
Data Engineer (Databricks)
wega Informatik —Berlin
- Vollzeit
- Informatik
- AWS
- Machine Learning
Senior Machine Learing Engineer on Databricks (m/w/d)
Würth-Gruppe —Berlin
- Teilzeit
- Azure
- Datenbanken
- SQL
- Flexible Arbeitszeiten
- Empfehlungsprogramm
Applied Scientist (all genders) - B2B Data Science and Algorithms
Zalando —Berlin
- Vollzeit
- Master
- SQL
- Machine Learning
11 Tage
Sr. Applied AI Engineer
Taktile —Berlin
- Vollzeit
- Hybrides Arbeiten
- Microsoft Excel
- Azure
- SQL
AI Engineer (m/w/d)
accantec group —Berlin
- Vollzeit
- Azure
- Englisch
- Master
Direkt bewerben
Robotics Engineer - Vision Language Action Model
Sensmore —Berlin
- Vollzeit
- Informatik
- Master
- C++
Direkt bewerben
AI Engineer – Computer Vision, AI Agents & Model Deployment (Part-Time)
YOONA Ventures GmbH —Berlin
- Teilzeit
- Forschungserfahrung
- AWS
- Machine Learning
Senior AI Engineer
Bluefish AI —Berlin
- Hybrides Arbeiten
- Master
- Künstliche Intelligenz
- Führungserfahrung
Data Scientist
Reflow —Berlin
- Vollzeit
- Homeoffice
- SQL
- Machine Learning
- Führungserfahrung
Direkt bewerben
Senior Applied Scientist (f/m/d)
Siemens —Berlin
- Vollzeit
- Hybrides Arbeiten
- Informatik
- Forschungserfahrung
- Master
8 Std.
Fraud Data Scientist
Billie —Berlin
- Vollzeit
- Hybrides Arbeiten
- Master
- SQL
- Machine Learning
- Homeoffice-Möglichkeit
- Flexible Arbeitszeiten
3 Std.
AI Working Student (Werkstudent) (Project-Based )
YOONA Ventures GmbH —Berlin
- Datenbanken
- AWS
- Machine Learning
Data Engineering Consultant - QuantumBlack, AI by McKinsey
McKinsey & Company —Berlin
- Azure
- Informatik
- SQL
Lead AI Engineer (f/m/x) – Chief Strategy Office
Deutsche Bank —Berlin
- Vollzeit
- Hybrides Arbeiten
- Doktorat
- Master
- Machine Learning
7 Tage

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machine learning engineer jobs near berlin

ML Ops Engineer

Zeta Global -
Berlin

Jetzt bewerben

Details zur Stelle

vor 10 Tagen

Leistungen

Flexible Arbeitszeiten

Qualifikationen

TensorFlow
CI/CD
Informatik
PyTorch
Spark
Wartung
Master
SQL
AWS
Docker
Machine Learning
APIs
Agile
gRPC
GitLab
Python

Vollständige Stellenbeschreibung

WHO WE ARE

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.

The Role

We’re looking for a skilled ML Engineer / Data Scientist with 3+ years of software or applied ML experience to design, build, and improve machine learning solutions in a dynamic cloud environment, primarily on AWS.This role sits at the intersection of data science and engineering: exploring data, developing models, running rigorous experiments, and bringing the best approaches into production with a reliable, reproducible workflow. If strong Python skills, curiosity about hard modeling problems, and collaborative work in multicultural teams are a fit, this is a chance to do meaningful, end-to-end ML work—not just notebooks, and not just infrastructure.

Who you are:

Strong foundation in machine learning, statistics and experiment design.
Experience building models for real business or product problems, not only academic benchmarks.
Comfortable working with structured and unstructured data: feature engineering, dataset construction, labeling quality, leakage checks, and train/validation/test discipline.
Able to compare approaches with clear metrics, error analysis, and sound judgment about tradeoffs (accuracy, latency, cost, maintainability).
Interest in modern ML, including classical ML, deep learning, and LLM / GenAI workflows where relevant (fine-tuning, RAG, evaluation, prompt/versioning).
Proficient in Python and able to write clean, modular, testable code.
Experience developing and deploying ML solutions in a cloud environment, especially AWS.
Comfortable moving from prototype to production: packaging models, building inference paths, monitoring performance, and iterating after launch.
Independent engineer who can own work from problem framing experimentation implementation rollout.
Excellent written and spoken English.
Enjoy working closely with engineers, product partners, and other data scientists.
Clear communicator who can explain methods, results, and limitations to technical and non-technical audiences.
Master’s degree in Science or Engineering (Computer Science, Mathematics, Physics, Statistics, or similar), or equivalent practical experience.

Nice to have:

Experience with scikit-learn, PyTorch, TensorFlow, XGBoost, or similar modeling stacks.
Familiarity with ML experiment tracking and reproducibility (e.g. MLflow, W&B).
Experience with SQL, data warehouses/lakes, and pipeline tools such as Airflow, dbt, or Spark.
Exposure to feature stores, embedding pipelines, or vector search for retrieval-based systems.
Experience building HTTP/gRPC APIs or lightweight services around model inference.
Working knowledge of Docker, basic orchestration, and CI/CD (e.g. GitLab CI).
Experience in agile, remote and async team environments.
Publications, patents, Kaggle/competition results, or open-source ML contributions.

What you might like about this role:

Hands-on modeling work with room to explore, benchmark, and improve real systems.
Collaboration on ML patent submissions and participation in weekly ML / research paper review meetings.
A multicultural, engineering-focused team with strong peer support.
High trust and autonomy—clear goals, freedom in how to reach them.
Internal product impact: meaningful projects that improve developer and user experience, not endless maintenance tickets.
Short approval cycles and solid product partnership.
A healthy meeting policy and emphasis on protecting focus time.
Flexible hours, remote/home office options, and a calm, engineers-only office when on-site.
Competitive compensation, including stock options.

We’re hiring across multiple levels. Title, scope, and compensation depend on experience—from strong applied ML generalists to senior people who can lead modeling direction and mentor others.

We’re especially interested in candidates who are technically strong, intellectually curious, and motivated by difficult, ambiguous problems where good data science and solid engineering both matter.

PEOPLE & CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.

We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here: https://zetaglobal.com/blog/a-look-into-zetas-ergs/

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases

#LI-NP1

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Erweiterte Suche

machine learning engineer Jobs in berlin

ML Ops Engineer

Applied Scientist (f/m/d)

Biomarker Data Scientist (all gender)

Quereinsteiger Physiker / Mathematiker als Software Engineer Data & AI (mwd)

Data Scientist

AI Engineer

Data Engineer (Databricks)

Senior Machine Learing Engineer on Databricks (m/w/d)

Applied Scientist (all genders) - B2B Data Science and Algorithms

Sr. Applied AI Engineer

AI Engineer (m/w/d)

Robotics Engineer - Vision Language Action Model

AI Engineer – Computer Vision, AI Agents & Model Deployment (Part-Time)

Senior AI Engineer

Data Scientist

Senior Applied Scientist (f/m/d)

Fraud Data Scientist

AI Working Student (Werkstudent) (Project-Based )

Data Engineering Consultant - QuantumBlack, AI by McKinsey

Lead AI Engineer (f/m/x) – Chief Strategy Office

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