10 beste Stellen als machine learning engineer in berlin mitte, be – aktuell auf Personalsuche

Senior Machine Learning Engineer (m/f/*)
Peregrine Technologies GmbH —Berlin
- Montag bis Freitag
- C++
- Machine Learning
- APIs
- Flexible Arbeitszeiten
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2 Tage
Junior AI Engineer (m/f/d)
Artefact —Berlin
- Vollzeit
- Azure
- Informatik
- Master
- Flexible Arbeitszeiten
9 Std.
Berater für Digitale Transformation & KI (m/w/d) – Ideal für Quereinsteiger
mycareernow GmbH —Falkensee
- Ab 50.000 € pro Jahr
- Teilzeit
- Homeoffice
- Machine Learning
- PC-Kenntnisse
- Künstliche Intelligenz
- Weiterbildungsprogramme
Direkt bewerben
SENIOR CONSULTANT - DATA ENGINEERING & AI DATA PRODUCTS (M/W/D)
Berlin, München —Berlin
- Hybrides Arbeiten
- Azure
- Englisch
- SQL
- Weiterbildungsprogramme
13 Tage
Data Scientist
JINGDONG RETAIL (UK) LIMITED —Berlin
- Vollzeit
- Azure
- Datenanalyse
- Master
Direkt bewerben
1 Tag
Senior Data Engineer - Google Cloud Platform Berlin (m/w/d)
Schwarz Corporate Solutions —Berlin
- Vollzeit
- Englisch
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Wolt - English —Berlin
- Homeoffice
- Doktorat
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- Machine Learning
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5 Tage
Senior AI Engineer (m/f/d)
Artefact —Berlin
- Vollzeit
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- Flexible Arbeitszeiten
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Data Scientist (m/w/d) // Remote möglich
E. Breuninger GmbH & Co. —Berlin
- Per E-Mail
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- Englisch
- Homeoffice-Möglichkeit
Direkt bewerben
2 Tage
Data Engineer (all genders)
GROPYUS —Berlin
- Machine Learning
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1 Std.

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machine learning engineer jobs near berlin mitte, be

Senior Machine Learning Engineer (m/f/*)

Peregrine Technologies GmbH
Berlin

Direkt bewerben

Details zur Stelle

vor 2 Tagen

Leistungen

Firmenevents
Flexible Arbeitszeiten

Qualifikationen

TensorFlow
PyTorch
C++
Machine Learning
APIs
Keras
Künstliche Intelligenz
Python

Vollständige Stellenbeschreibung

About Peregrine

Based in Berlin, we're leveraging the power of AI to transform cameras into intelligent devices, enhancing road safety and urban mobility on a global scale, while preserving privacy at all times.

At Peregrine, diversity and international collaboration fuel innovation. We unite the brightest minds with strong academic backgrounds and rich industry experience in robotics and machine learning, spanning from the tech hubs of Silicon Valley to the engineering powerhouses of Europe. Our team boasts alumni from leading automotive giants like Bosch, Volkswagen, IAV, and TomTom and institutions such as the ETH in Zurich. We're on the hunt for brilliant, dynamic, and passionate individuals eager to tackle challenging problems and make a tangible impact.

Tasks

The Role

As a Senior Machine Learning Engineer, you will own the design, training, and on-device deployment of the computer vision models at the heart of our product. You will work at the intersection of research and production, turning state-of-the-art vision techniques into reliable systems that run within strict latency and privacy constraints on resource-constrained edge hardware. Your key tasks will include:

Design, train, and optimize deep learning models for object detection, semantic segmentation, pose estimation, and tracking.
Port and deploy models to resource-constrained edge hardware, achieving single-digit millisecond latency without cloud dependencies.
Build and maintain robust vision pipelines from data ingestion through training to production inference.
Apply model compression techniques such as quantization, pruning, knowledge distillation, and neural architecture search to meet strict performance budgets.
Develop synthetic data and domain adaptation pipelines to close the sim-to-real gap.
Profile inference pipelines end-to-end to identify and eliminate bottlenecks on target silicon.
Translate cutting-edge academic research into highly reliable, production-grade systems.
Collaborate closely with hardware, product, and research colleagues to shape our privacy-by-design architecture.

Requirements

Your Profile

Core Competencies: Computer Vision & Edge AI

Edge AI & On-Device Inference: Expertise in porting, deploying, and optimizing complex deep learning models for local, resource-constrained hardware without cloud dependencies.
Advanced Computer Vision: Deep knowledge of developing vision pipelines for object detection, semantic segmentation, pose estimation, and tracking.
Hardware-Aware Architecture Design: Ability to custom-build network topologies tailored to specific sensors and strict latency budgets, rather than relying on off-the-shelf APIs.
Synthetic Data & Domain Adaptation: Proven experience in building simulation pipelines for synthetic data generation and closing the “sim-to-real” gap using Domain Randomization and GANs.

Technical Stack & Tools

Languages: Advanced proficiency in C++ (for production-grade edge deployment) and Python (for training, research, and data analysis).
AI/ML Frameworks: Extensive hands-on experience with PyTorch, and TensorFlow / Keras.
Optimization & Deployment: Mastery of inference acceleration and model conversion using TensorRT, ONNX, and OpenVINO.
Model Compression: Practical application of quantization, pruning, knowledge distillation, and neural architecture search.

System Architecture & Compliance

Privacy-by-Design Architecture: Designing robust, local AI systems that guarantee data sovereignty and strict GDPR compliance without cloud roundtrips.
Performance Profiling: Deep-dive auditing of inference pipelines to identify bottlenecks and achieve single-digit millisecond latency on target silicon.

Research, Strategy & Leadership

Research-to-Production (R2P): The ability to translate complex, state-of-the-art academic research into highly reliable systems that work in the real world.
AI Strategy & Assessment: Capability to conduct feasibility studies, ROI analysis, and privacy-first architecture blueprinting.

Mindset

Comfort with ambiguity, a problem-solving mindset, and adaptability to rapid change.
Entrepreneurial drive, a strong sense of responsibility, high ambition, and a collaborative approach to achieving goals.
Excellent verbal and written communication skills in English and the ability to effectively collaborate with various stakeholders.
Having work experience in a startup or venture capital is a plus.

We don’t expect anyone to check all these boxes mentioned above! If a few of these points apply to you, we want to talk!

Benefits

Our offering

The opportunity to significantly contribute to the company's growth and success.
A competitive salary.
An evolving role that grows with our company's journey.
We have flexible working hours and a need-based work-from-home policy; all processes are being set up for remote first.
A diverse and inclusive work environment as well as a flat organizational structure, fast decision making within the team, disagree & commit.
We foster a culture where we all learn from each other and value new ideas.
We hold fun team events throughout the year.
We contribute to your monthly public transport ticket.
Free drinks, snacks, and coffee.

Direkt bewerben

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