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

ML Ops Engineer
Zeta Global —Berlin
- Informatik
- Wartung
- Master
- Flexible Arbeitszeiten
Direkt bewerben
18 Std.
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18 Std.
Senior Applied Scientist (All genders)
Zalando —Berlin
- Vollzeit
- Hybrides Arbeiten
- Doktorat
- Master
- Python
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11 Tage
Data Engineering Consultant - QuantumBlack, AI by McKinsey
McKinsey & Company —Berlin
- Azure
- Informatik
- SQL
9 Tage
Data Scientist/ML Engineer (m/f/d)
WebMD —Berlin
- Vollzeit
- SQL
- Machine Learning
- Python
- Homeoffice-Möglichkeit
- Mitarbeiter-Rabatt
Direkt bewerben
Lead Data Scientist, Revenue - Ads, Revenue
Vinted —Berlin
- 90.100 € – 132.500 € pro Jahr
- Machine Learning
- Python
- Employee Assistance Program
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Senior AI Software Engineer – Model Training (f/m/d)
Aleph Alpha —Berlin
- Vollzeit
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- Informatik
- Master
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14 Tage
AI Working Student (Werkstudent) (Project-Based )
YOONA Ventures GmbH —Berlin
- Datenbanken
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Zalando —Berlin
- Vollzeit
- Master
- SQL
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1 Tag
Applied Scientist – Marketing & Personalization
Zalando —Berlin
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4 Tage
Senior ML Research Engineer – AI & Generative Recommendation (m/f/d)
adjoe —Berlin
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10 Tage
Data Scientist (m/f/x)
Enpal —Berlin
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Senior Applied Scientist - Assortment Demand Forecast (all genders)
Zalando —Berlin
- Vollzeit
- Hybrides Arbeiten
- Doktorat
- Master
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Senior Data Scientist
Smartly.io —Berlin
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Robotics Engineer - Vision Language Action Model
Sensmore —Berlin
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Principal Applied Scientist / Lounge by Zalando (all genders)
Zalando —Berlin
- Vollzeit
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14 Tage
Senior Data Platform Engineer (d/f/m)
Taxfix —Berlin
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AI Engineer (Agentic AI & LLM Systems)
beroe x nnamu GmbH —Berlin
- Vollzeit
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- APIs
- Flexible Arbeitszeiten
Direkt bewerben
Applied Scientist III, AFT AI, Amazon AFT AI
Amazon Development Center Germany GmbH —Berlin
- Vollzeit
- Doktorat
- Forschungserfahrung
- Master
11 Tage

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ML Ops Engineer

Zeta Global -
Berlin

Direkt bewerben

Details zur Stelle

vor 18 Stunden

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

Direkt bewerben

Erweiterte Suche

machine learning engineer Jobs in berlin

ML Ops Engineer

Foundation and generative models for biomolecules

Biomarker Data Scientist (all gender)

Senior Applied Scientist (All genders)

Data Engineering Consultant - QuantumBlack, AI by McKinsey

Data Scientist/ML Engineer (m/f/d)

Lead Data Scientist, Revenue - Ads, Revenue

Senior AI Software Engineer – Model Training (f/m/d)

AI Working Student (Werkstudent) (Project-Based )

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

Applied Scientist – Marketing & Personalization

Senior ML Research Engineer – AI & Generative Recommendation (m/f/d)

Data Scientist (m/f/x)

Senior Applied Scientist - Assortment Demand Forecast (all genders)

Senior Data Scientist

Robotics Engineer - Vision Language Action Model

Principal Applied Scientist / Lounge by Zalando (all genders)

Senior Data Platform Engineer (d/f/m)

AI Engineer (Agentic AI & LLM Systems)

Applied Scientist III, AFT AI, Amazon AFT AI

Ich möchte aktuelle Job-E-Mails für Stellen als machine learning engineer in berlin erhalten

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