senior data engineer

data scientist

data engineer

founding software engineer (backend, cloud & ai infrastructure) Jobs in Berlin

full stack engineer

deep learning engineer

Audible

<div>
 
 Description
 
 
 
 At Audible, we believe stories have the power to transform lives. It&rsquo;s why we work with some of the world&rsquo;s leading creators to produce and share audio storytelling with our millions of global listeners. We are dreamers and inventors who come from a wide range of backgrounds and experiences to empower and inspire each other. Imagine your future with us.
 
 
 
 About This Role
 
 
 
 As an Applied Scientist, you will solve large complex real-world problems at scale, draw inspiration from the latest science and technology to empower undefined/untapped business use cases, delve into customer requirements, collaborate with tech and product teams on design, and create production-ready models that span various domains, including Machine Learning (ML), Artificial Intelligence (AI) and Generative AI, Natural Language Processing (NLP), Reinforcement Learning (RL), real-time and distributed systems.
 
 
 
 About You
 
 
 
 Your work will focus on inventing or adapting scientific approaches, models, and algorithms driven by customer needs at the project level. You will develop components and/or end-to-end solutions that are deployed into production or directly support production systems, delivering consistently high-quality work that meets both scientific and engineering best practices. You will develop reusable science components and services that resolve architecture deficiencies and customers&rsquo; pain points, while making technical trade-offs for long-term/short- term. You will work semi-autonomously to deliver solutions, contribute to research papers at peer-reviewed venues when appropriate, and document your work thoroughly to enable others to understand and reproduce it. Your decision-making will consistently incorporate robust, data-driven business and technical judgment. You will collaborate with other scientists to raise the bar of both scientific and engineering complexity for the team and to foster valuable scientific partnership opportunities to help/guide science decisions. We work in a highly collaborative, fast-paced environment where scientists, engineers, and product managers work to test and build scalable foundational capabilities, as well as customer facing experiences. You will have the opportunity to innovate and think big within your projects scope, implement optimization services and algorithms, and influence the experiences of millions of customers. We are looking for a results-oriented Applied Scientist with deep knowledge in ML, NLP, Deep Learning, GenAI, and/or large-scale distributed computation.
 
 
 As an Applied Scientist, you will...
 
 
 <ul>
 <li>
 Understand use cases across the business and adopt/extend/design/invent solutions/models that are scalable, efficient, and automated for difficult problems that are not well defined
 </li>
 <li>
 Work closely with fellow scientists and software engineers (at Audible and Amazon) to build and productionize models, deliver novel and highly impactful features
 </li>
 <li>
 Review models of peers for the purpose of reducing and managing risk to the business, while improving customer experience
 </li>
 <li>
 Design, develop, and deploy modeling techniques and solutions for Content Understanding, Recommendations, GenAI-based product features, by employing a wide range of methodologies, working from simple to complex
 </li>
 <li>
 Contribute to initiatives that employ the most recent advances in ML/AI in a fast-paced, experimental environment
 </li>
 <li>
 Push the boundary of innovation
 
 
 </li>
 </ul>
 
 About Audible
 
 
 
 Audible is the leading producer and provider of audio storytelling. We spark listeners&rsquo; imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers daily lives. We are a global company with an entrepreneurial spirit. We are dreamers and inventors who are passionate about the positive impact Audible can make for our customers and our neighbors. This spirit courses throughout Audible, supporting a culture of creativity and inclusion built on our People Principles and our mission to build more equitable communities in the cities we call home.
 
 
 
 Basic Qualifications
 
 
 
 <ul>
 <li>
 3+ years of building models for business application experience
 </li>
 <li>
 PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
 </li>
 <li>
 Experience in patents or publications at top-tier peer-reviewed conferences or journals
 </li>
 <li>
 Experience programming in Java, C++, Python or related language
 </li>
 <li>
 Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
 </li>
 <li>
 MSc + 5ys of relevant experience, or PhD +1 year in one of the following disciplines: Machine Learning, Computer Science, Computer Engineering, Data Science, Applied Math, or a related quantitative field
 </li>
 <li>
 3+ years of experience in Deep Learning, Natural Language
 </li>
 <li>
 Processing/Understanding, GenAI and/or Reinforcement Learning
 </li>
 <li>
 Proficiency in Python, SQL, and other scripting languages
 </li>
 <li>
 Experience employing and innovating with LLMs/GenAI to solve complex problems
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience using Unix/Linux
 </li>
 <li>
 Experience in professional software development
 </li>
 <li>
 Experience with building Recommendation Systems
 </li>
 <li>
 Machine Learning Pipeline orchestration with AWS (SageMaker, Batch, Lambda, Step Functions) or similar cloud-platforms
 
 
 </li>
 </ul>
 Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
 
 
 m/w/d
 
 
 Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.
 
 
 
 
 Company
 
 - Audible GmbH - B38
 
 
 Job ID: A10450357
</div>

Applied Scientist

ALMETRA

<div>We&rsquo;re looking for a Research Engineer to push the limits of vision-language models for real-world video understanding. You&rsquo;ll work on applied, state-of-the-art multimodal models and turn them into production pipelines used by customers.<h3 class="jobSectionHeader">
Your role</h3><ul><li>
Design and adapt vision-language and video models for scene understanding, temporal reasoning and activity / action recognition</li><li>
Build and maintain large-scale training and evaluation pipelines on GPU clusters</li><li>
Curate and augment video-text and action datasets, including synthetic labels and retrieval-based augmentation</li><li>
Develop robust benchmarks for video QA, instruction following and temporal understanding, and use them to drive iterative model improvements</li><li>
Cut and refactor model architectures for efficiency and deployability (compression, pruning, distillation)</li><li>
Deliver production-ready inference pipelines to product and customer teams, working closely with CV, platform and robotics engineers</li></ul><h3 class="jobSectionHeader">
You bring</h3><ul><li>
Completed PhD (or equivalent research track record) in computer vision, machine learning, robotics or a related field</li><li>
Strong background in video-centric deep learning: scene understanding, temporal / activity / action recognition, or video generation</li><li>
Experience training and adapting large vision or VLM models (e.g. InternVL, Qwen-VL, DeepSeek-VL, similar stacks)</li><li>
Proven work with multi-GPU training (PyTorch, distributed, mixed precision) and large-scale datasets</li><li>
Solid engineering habits: clean Python, reproducible experiments, reliable data and training pipelines</li><li>
Track record of moving research into usable systems (demos, internal tools, or productised features) in fast-moving teams</li></ul><h3 class="jobSectionHeader">
Nice to have</h3><ul><li>
Publications at top-tier venues (CVPR, ICCV, ECCV, NeurIPS, ICLR, etc.) on video, multimodal learning or scene understanding</li><li>
Experience with 3D/4D scene representations, action generation or embodied / sense-plan-act style projects</li><li>
Inference optimisation: quantisation, TensorRT, model distillation, or deployment on constrained hardware</li><li>
Prior experience in a startup or applied research lab environment</li></ul>
What we offer
Employee Share Options Program for all permanent employees*
An increasing benefits list: currently includes Urban Sports club and quarterly team retreats.
Be on the forefront in defining what artificial intelligence means in manufacturing
Gain hands-on experience in working in an AI-first software company
Supportive and inclusive culture that values diversity and promotes the advancement of underrepresented groups within the company
Collaborate with a diverse (currently more than 10 nationalities) and talented team, working on cutting-edge projects with real-world impact
Network with professionals and leaders in the field, opening doors to potential future career opportunities
We have a very flat hierarchy, open 360&deg; feedback, and flexible working hours
Ethics: We are committed to developing ethical AI software 
 
Don't meet all the requirements?
Almetra is committed to creating a workplace that is diverse, fair, and inclusive. We encourage candidates from all backgrounds, even if they do not meet every qualification, to submit their application. We firmly believe that having a team with diverse perspectives only strengthens our company and drives innovation. Our commitment also extends to providing an accessible environment for everyone, including those with disabilities. Please let us know if you require any accommodations during the application process or while working with us, and we will do our best to support you.<ul><li> 
Only full-time, permanent roles are eligible for stock options. Part-time roles, contract roles, work-student, internships and freelance roles are not eligible for stock options.</li></ul></div>

VLM Research Engineer (m/f/d)

Norwegian Refugee Council

<div>What we are looking for:
We're looking for an experienced Data Scientist to help shape the future of humanitarian action through CLEAR (Crisis Learning, Early Warning and Anticipatory Action) - NRC's open infrastructure designed to transform fragmented crisis data into timely, actionable intelligence. 
CLEAR brings together diverse data sources - including earth observation, conflict data, field reports, and market intelligence - into a shared, open, and federated platform that enables humanitarian teams to anticipate crises and act before they escalate. By closing the gap between insight and action, CLEAR empowers faster, smarter, and more effective humanitarian responses. 
As the Data Scientist, you will play a pivotal role in designing and deploying cutting-edge machine learning and deep learning solutions that support early warning systems and humanitarian decision-making. You will develop predictive models capable of identifying emerging crisis patterns, forecasting humanitarian needs, and transforming complex, multimodal datasets into practical insights for field operations.
This is a highly technical, hands-on role suited to someone who enjoys building, training, and fine-tuning AI models from the ground up. You are comfortable working in data-scarce, rapidly evolving environments, proactively sourcing and preparing data, and solving complex challenges where real-world impact matters.
Working closely with the AI Lead, software developers, and data engineers, you will contribute across the full machine learning lifecycle - from model development and optimisation to performance monitoring and deployment. You will also help shape the technical environment in which models are trained and refined, ensuring AI solutions are scalable, robust, and aligned with the operational realities of humanitarian response. 
What you will do:
Here are some of your specific responsibilities
<ul><li>Support the design and implementation of CLEAR&rsquo;s data architecture.
</li><li>Partner with developers and data engineers to design and stand up the environment needed to train and fine-tune models (including data ingestion pipelines, compute and GPU resources, experiment tracking and MLOps tooling) actively shaping that environment rather than waiting for it to be provided.
</li><li>Develop machine learning and deep learning models that integrate multiple data streams to detect early indicators of humanitarian crises, combining earth observation and satellite imagery, conflict event data, climate monitoring, economic indicators, and population movement patterns into unified risk assessment frameworks.
</li><li>Build computer-vision and remote-sensing models on satellite and aerial imagery (for example flood-extent mapping, building and settlement detection, displacement-site monitoring, infrastructure damage assessment and land-cover change detection) and fuse these earth observation outputs with non-imagery signals.
</li><li>Contribute to building automated alert systems that identify emerging crises, calibrating prediction algorithms for different crisis types.
</li><li>Create ensemble modelling approaches that combine traditional statistical methods with advanced AI techniques.
</li><li>Fine-tune and adapt foundation models and large language models to humanitarian use cases such as document triage, multilingual report analysis and situation summarisation.
</li><li>Explore venues for adapting models to evolving crisis conditions through reinforcement learning systems.
</li><li>Implement impact-based forecasting systems that translate meteorological, conflict, and economic predictions into specific humanitarian consequences such as displacement volumes, food insecurity levels, and infrastructure damage estimates.
</li><li>Build decision trees and recommendation engines that guide field staff through systematic needs assessment processes informed by predictive analytics and historical response data.
</li><li>Create automated reporting systems and interactive dashboards that enable field teams and leadership to access real-time data for rapid response activities.
</li><li>Any other tasks assigned by the CLEAR Technical Lead and AI Lead related to CLEAR data.
</li></ul>Please download the detailed job description to learn more about this position.
What you will bring:
<ul><li>Advanced degree in Data Science, Statistics, Computer Science, Physics, Engineering, Economics or a related quantitative field, with a minimum of 5 years of professional experience in applied data science.
</li><li>Demonstrated experience designing, training and fine-tuning deep learning models (e.g. CNNs, recurrent/sequence models and transformers), including how to structure training runs, manage compute, and diagnose and improve model performance.
</li><li>Advanced proficiency in Python for statistical analysis, machine learning and data manipulation, with experience in key libraries including pandas, NumPy, scikit-learn, TensorFlow, PyTorch and Keras.
</li><li>Strong SQL skills for database management and complex query optimization.
</li><li>Hands-on experience implementing supervised and unsupervised learning algorithms including regression models, classification techniques, clustering methods, and time series analysis.
</li><li>A proven track record of proactively sourcing and engineering data (finding, negotiating access to, cleaning and, where necessary, generating data).
</li><li>Experience designing and implementing ETL pipelines for processing datasets from multiple sources, with skills in data cleaning, transformation and quality assurance at scale.
</li><li>Ability to create automated reporting systems and dashboards using tools like Tableau, Power BI or similar platforms.
</li><li>Experience working with large, messy, real-world datasets.
</li><li>Understanding of model deployment and MLOps practices, and comfort working with engineers to provision the infrastructure models need.
</li><li>Fundamental skills with version control software and collaborative development.
</li><li>Fluency in written and spoken English. Other languages are an asset.
</li><li>Practical experience working in low-data or data-scarce settings, including transfer learning, few-shot learning, data augmentation and synthetic data generation to overcome limited training data.
</li><li>Experience implementing and fine-tuning large language models (LLMs) for applied tasks.
</li><li>Experience with natural language processing techniques for analyzing reports, social media or news data relevant to crisis monitoring.
</li><li>Experience using GenAI for automated analysis of large volumes of documents &mdash; extracting key themes, sentiment analysis and identifying emerging trends across multiple contexts and languages.
</li><li>Understanding of ensemble methods and explainable AI techniques for transparent decision-making.
</li><li>Experience working with earth observation and satellite imagery; optical (e.g. Sentinel-2, Landsat) and radar / SAR (e.g. Sentinel-1), alongside commercial high-resolution sources, and with geospatial tooling such as Google Earth Engine, rasterio / GDAL, xarray and geopandas.
</li><li>Applying computer vision and deep learning to imagery (semantic segmentation, object detection, change detection) for humanitarian tasks such as flood-extent mapping, damage assessment, settlement and displacement-site detection, infrastructure monitoring and population estimation (a strong asset).
</li><li>Experience with multimodal data fusion.
</li></ul>What we offer:
<ul><li>Duty station: Remote (Germany, France, UK or Belgium)
</li><li>Contract: Fixed term (2 years)
</li><li>Travel: Up to 10%
</li><li>Salary/benefits: Grade 9 on NRC&rsquo;s Resident salary scale, with accompanying terms and conditions.
</li><li>NRC is an equal opportunities employer. We are committed to diversity without distinction to age, gender, religion, ethnicity, nationality, and physical ability.
</li><li>We think outside the box, encourage ideas, and give responsibility to all employees at all levels. You will have many opportunities to be heard and take the initiative.
</li></ul>Find out more about the benefits of working for NRC
Important information about the application process
<ul><li>For Internal candidates: To apply as an internal candidate, log in with your official email or click on Opportunity Market Place.
</li><li>When creating your profile, include your full name as given on your passport. Complete all the system-required fields for experience, employment history and education.
</li><li>Submit your application and CV in English, taking care to attach your latest CV.
</li><li>Applications that do not meet the minimum standards in terms of experience or qualifications will generally not be considered. Unsolicited applications not related to this specific job advertisement will not be considered.
</li><li>We receive many applications for each vacant position and so only shortlisted candidates will be contacted.
</li></ul>If you have any questions about this role, please email ho.recruitment@nrc.no with the job title as the subject line.
Why NRC?
The Norwegian Refugee Council (NRC) is an independent humanitarian organisation helping people forced to flee. Our 15,000 staff work in crises across 40 countries, providing life-saving and long-term assistance to millions of people every year.
Watch this short video to see NRC in action.
We are looking for people who are passionate about helping refugees and people forced to flee. Are you one of those people? If you are, NRC offers you the opportunity to:
<ul><li>do demanding and professional work, often in challenging contexts.
</li><li>join a work culture that empowers every employee to share ideas and take responsibility.
</li><li>be part of a welcoming and supportive community committed to human dignity.</li></ul></div>
 <div><div>The Norwegian Refugee Council (NRC) is a global humanitarian organisation helping people forced to flee. 
</div><div></div> 
<div>Join us in assisting millions of people in areas where others cannot, tackling some of the world's most dangerous and difficult crises. Bring your skills and dedication to an organisation recognised for providing high quality aid and for defending the rights of refugees and internally displaced people. 
</div><div></div> 
<div>At NRC, we give responsibility to employees at all levels and foster professional growth and innovative teams. You can expect a supportive culture and an open dialogue with management. We are committed to diversity, equity and inclusion. 
</div><div></div> 
<div>Together, we save lives and rebuild futures. 
</div><div></div> 
<div>Safeguarding is central to NRC&rsquo;s work. We expect all employees to:
</div><ul><li>treat everyone with respect and dignity
</li></ul><ul><li>contribute to building a safe environment for all
</li></ul><ul><li>never engage in any form of exploitation, harassment and specifically sexual exploitation, abuse and sexual harassment (SEAH)
</li></ul><ul><li>always report. NRC has a zero-tolerance approach to inaction against exploitation, abuse and SEAH</li></ul></div>

Data Scientist

adjoe

<div>adjoe builds the technologies behind mobile app growth and monetization, challenging the status quo of adtech by redefining how apps acquire users and generate revenue. Our two products, Playtime Arcade and adjoe Ads, sit at opposite ends of the mobile advertising spectrum: rewarded engagement and programmatic in-app advertising. Together they run on 13% of the world's smartphones, connecting advertisers, publishers, and hundreds of millions of users, with one goal: making mobile advertising work better for everyone in the ecosystem.
Next-Gen Machine Intelligence for Scalable Discovery &amp; Engagement
The Data Science Research team builds foundational ML representations and advanced AI capabilities that enhance both Playtime and adjoe Ads. Operating as a horizontal deep-tech layer, the team leverages advanced AI and deep learning approaches&mdash;specifically generative approaches &mdash;to deliver critical systems such as high-dimensional user embeddings, general content understanding and sequential recommendation. These frameworks scale adjoe's products beyond standard industry limitations, utilizing behavioral and transactional data from over 770 million users.
The team operates at the intersection of bleeding-edge R&amp;D and high-scale production engineering, acting as the company&rsquo;s internal science bar raiser and primary consulting layer for complex ML bottlenecks. The stack is optimized for deep learning and heavy data throughput: PyTorch and [Ray/Hugging Face] for training and fine-tuning foundation models, Trino and Athena for querying massive user-behavior data lakes, and dedicated GPU infrastructure for heavy workloads. The full lifecycle of these AI capabilities is owned by the team&mdash;from academic paper translation and offline prototyping to deploying core algorithmic frameworks built to sustain high-throughput, realtime production environments.
Your Mission &amp; Who We Are Looking For:<ul><li>
PhD or equivalent research depth, with a track record of technical mentorship. PhD in CS, Statistics, Math, or Physics. Publications in SIGIR, KDD, NeurIPS, or ICLR, and 5+ years building large-scale recommender systems in AdTech, e-commerce, or social. You've owned architectural bets and had accountability for outcomes.</li><li>
You set the research direction. You identify the highest-leverage problems at the intersection of generative AI and recommendation, define the multi-quarter research agenda, and align engineering and product leadership. That means owning how Generative Retrieval, Deep Ranking, and Re-ranking evolve across a stack built on 770 million users' behavioral data.</li><li>
Deep expertise in PyTorch and large-scale model optimization. Hands-on with high-concurrency optimization, quantization, and distillation &mdash; getting large generative models to run under extreme production constraints, not just in research environments.</li><li>
You are the company's deepest resource on generative recommendation. You translate SOTA research into systems adjoe can ship, review architectural decisions across teams, and raise the ML quality bar company-wide. When there's a hard bottleneck, you're the first call.</li><li>
You grow the teams around you. You mentor senior and mid-level scientists, lead architectural debates, and drive long-horizon investments without needing a roadmap handed to you.</li></ul>
We welcome applications from talent worldwide and provide relocation support to Hamburg, Germany for those ready to join our team.
What&rsquo;s in It for You?
At adjoe, you&rsquo;re not here to just close JIRA tickets, you&rsquo;re helping build the infrastructure behind one of the most impactful platforms in adtech. The systems you work on will reach hundreds of millions of users and power billions of decisions every day.<ul><li>
Go Big. Own projects with impact on 770M users and push adtech boundaries.</li><li>
Move Fast. Ship solutions multiple times a day, learn from results, and keep momentum.</li><li>
Be Direct. Solve problems openly and collaborate across teams.</li><li>
Thrive Together. Grow with a diverse, global team of people from over 40 different countries that learn from each other.</li><li>
Have Fun. Celebrate wins, enjoy daily victories, and bring your energy.</li></ul>
We welcome applications from people who will contribute to the diversity of our company.</div>

Staff ML Research Scientist (m/f/d)

RoboService

<div>
 
 
 Company Description
 
 
 
 RoboService solves the "Last Mile" of humanoid robotics. While manufacturers provide the hardware and foundation models, these general-purpose "brains" are not yet ready for the specific, accurate tasks of a production line. We bridge that gap.
 
 
 
 
 
 We don't build foundation models from scratch; we operationalize them. We take state-of-the-art VLA models and fine-tune them for reliability, speed, and precision in real-world manufacturing environments.
 
 
 
 
 
 We are not a research lab; we are shipping code that moves atoms. Launched in July 2025 by repeat founders with successful exits, we are looking for engineers who want to take robots out of the lab and onto the factory floor.
 
 
 
 
 
 
 Role Description
 
 
 
 We are looking for an intern / working student who joins our Robotics Machine Learning Engineering team. You will bridge the gap between "remote controlled hardware" and "autonomous robots". We work with robotics manufacturers that provide great hardware and a model infrastructure, but are missing the software to fine-tune the models on a specific task. Your primary focus will be establishing training pipelines - from teleoperation data collection to fine-tuning VLA models and utilizing Reinforcement Learning (RL) to fine-tune complex manipulation tasks.
 
 
 
 
 
 You won't be writing papers. You will be:
 
 
 
 
 <ul>
 <li>
 Building
 
 data pipelines
 
 to capture and analyze training data
 </li>
 <li>
 Fine-tuning
 
 VLA models
 
 (open source and proprietary models from our partners)
 </li>
 <li>
 Managing the
 
 Data Pipeline
 
 and overseeing the
 
 Teleoperation
 
 activities. Manage large datasets required for fine-tuning models.
 </li>
 <li>
 
 Reinforcement Learning
 
 (RL): Apply RL techniques to fine-tune robot actions, ensuring robust performance when the robot works on the production line.
 </li>
 <li>
 Utilize high-fidelity simulation environments (
 
 MuJoCo
 
 ,
 
 NVIDIA Isaac Sim, Omniverse
 
 ) to train and test agents before deploying them to physical hardware. (Sim2Real)
 </li>
 </ul>
 
 
 
 
 
 Qualifications
 
 
 <ul>
 <li>
 
 Education
 
 : Currently pursuing your Master&rsquo;s degree or PhD in Robotics, Computer Science, Data Science, Artificial Intelligence, or a related field.
 </li>
 <li>
 
 Experience
 
 : Machine Learning, Deep learning, or embodied AI. Hands-On Robotics Experience.
 </li>
 <li>
 
 Core ML Skills
 
 : Strong proficiency in Python and deep learning frameworks (PyTorch, TensorFlow, or JAX). Experience with Transformers and VLA architectures is highly desirable.
 </li>
 <li>
 
 Simulation
 
 : Proven experience with physics-based simulators, specifically NVIDIA Isaac Sim or similar (Gazebo, MuJoCo).
 </li>
 <li>
 
 Data Engineering:
 
 Ability to analyze and manage large datasets, automate data cleaning, and build training pipelines.
 </li>
 <li>
 Proficiency in
 
 English
 
 </li>
 </ul>
 
 
 
 
 
 What We Offer
 
 
 
 
 
 <ul>
 <li>
 
 Path to Full-Time
 
 : After a successful internship, we aim to extend a full-time offer.
 </li>
 <li>
 
 Berlin based
 
 : We&rsquo;re an in-person team and we work out of our office in downtown Berlin. If you're not in Berlin yet, be prepared to move here before the start of the job.
 </li>
 <li>
 
 Access to Cutting Edge Tech
 
 : Work daily on the latest software and hardware that will shape our future.
 </li>
 <li>
 
 Impact
 
 : Work in real projects with manufacturers to bring robots onto manufacturing floors.
 </li>
 <li>
 
 Startup Environment
 
 : We are a fast-moving startup with high growth ambitions.
 </li>
 <li>
 
 Team of Experts
 
 : We are a team of experts where every voice matters. Work with professionals that are leading their field.
 </li>
 </ul>
 
 
 
 
 
 Apply now!
 
 
</div>

Internship - Data Science & Robotics Machine Learning

The Formula

<div>Deine Benefits:<div><ul><li> 
Du arbeitest mit modernsten Technologien.</li><li>
Du wirst Teil eines Teams aus technikbegeisterten Engineers.</li><li>
Du begleitest das n&auml;chste Tech-Unicorn im Verteidigungssektor bei der Entwicklung eines der ersten multinationalen Drohnen-Fr&uuml;hwarnsysteme.</li><li>
Dich erwartet ein multinationales, pragmatisches Hands-on-Team mit starkem Innovationsfokus.</li><li>
Arbeite im B&uuml;ro in Berlin oder M&uuml;nchen &ndash; oder komplett im Homeoffice von &uuml;berall in der EU.</li><li>
Abgesehen von einigen Meetings arbeitest du dann, wann es f&uuml;r dich am besten passt.</li><li>
30 Tage Urlaub.</li><li>
Krankenversicherungspaket.</li></ul></div><div>
Deine Aufgaben:</div><div>
Du wirst Teil eines 35-k&ouml;pfigen Teams aus technikbegeisterten Sensorik-, IoT- und Hardware-Engineers. Gemeinsam mit deinen Kolleginnen und Kollegen &uuml;bernimmst du folgende Aufgaben:</div><div><ul><li>
Du bist Teil des Teams, das ein Ortungsprodukt der n&auml;chsten Generation mit lernender Kartenarchitektur baut.</li><li>
Du entwickelst Computer Vision Models (Dataset Preparation, Auto-Labeling, Training Optimization, Edge/Cloud Deployment) und implementierst die visuellen und akustischen Sensordaten in das System.</li><li>
Du verarbeitest multi-modale Sensordaten (Bilder, Radar, Akustik) unter schwierigen Feldbedingungen wie Jamming oder Sensor-Degradation.</li><li>
Du l&auml;sst Machine-Learning- und KI-Modelle direkt auf den lokalen Sensoren statt auf Cloud-Servern laufen und trainierst die Modellen direkt auf der Edge-Hardware (z. B. NVIDIA Jetson).</li><li>
Du implementierst skalierbare Modelle f&uuml;r Low-Latency-Anwendungen.</li><li>
Du kombinierst GPU-accelerated Vision Models (CUDA, TensorRT, DeepStream) mit skalierbaren backend services.</li><li>
Du arbeitest an real-time Networking von highly scalable Distributed Systems.</li><li>
Gemeinsam mit den Sensor Fusion Engineers, MLOps und DevOps Engineers erm&ouml;glichst du schnelle und sichere Deployments.</li><li>
Du &uuml;berwachst die Systeme, behebst St&ouml;rungen und verbesserst kontinuierlich die Observability.</li><li>
Wenn du m&ouml;chtest, unterst&uuml;tzt du Eins&auml;tze vor Ort, sammelst Sensordaten und validierst die Technologie in kontrollierten Feldversuchen.</li></ul> 
Dein Profil:</div><div><ul><li>
Aufgrund von Sicherheitsbestimmungen f&uuml;r diese Rolle ist die Staatsb&uuml;rgerschaft eines EU-Mitgliedstaates Voraussetzung.</li><li>
Du bist offiziell in einem EU-Land gemeldet.</li><li>
Mindestens 5 (ideal 10-15) Jahre Berufserfahrung im IT-Bereich (z. B. Software Engineering).</li><li>
Mindestens 2 (ideal 4-6)Jahre Vollzeit-Berufserfahrung als Machine Learning Engineer, idealerweise im Bereich Akustik.</li><li>
Mindestens 2 Jahre Berufserfahrung im IoT-Bereich.</li><li>
Flie&szlig;ende Kenntnisse in Python und den relevanten Frameworks.</li><li>
Gute Erfahrung mit dem Embedded-Linux-&Ouml;kosystem.</li><li>
Erste Cloud-Erfahrung.</li><li>
Du hast mindestens 2 Jahre am St&uuml;ck f&uuml;r denselben Arbeitgeber gearbeitet.</li><li>
Flie&szlig;endes Englisch; jede weitere gesprochene Sprache ist ein Plus.</li><li>
Du arbeitest gerne im Verteidigungssektor (Defense).</li><li>
Du bl&uuml;hst in einem dynamischen Startup- bzw. Scaleup-Umfeld auf.</li><li>
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Senior Machine Learning Engineer (d/m/w) Edge ML und IoT, Deutschland remote

NexTexAI

<div>
 
 NexTex AI is a Berlin-based deep-tech startup building an AI-powered intelligence layer for textile manufacturing.
 
 
 
 Our platform combines industrial cameras, retrofit sensors, PLC/SCADA signals, edge computing and artificial intelligence to detect textile defects, optimize production processes and generate sustainability KPIs for CSRD and EU Green Deal compliance.
 
 
 
 We are currently preparing our EXIST Startup Grant application and a ProFIT Berlin R&amp;D funding application. Our goal is to build and validate an MVP with pilot textile manufacturers during the first year and scale into one of Europe's leading industrial AI platforms for textile production.
 
 
 
 We are looking for a Founding Software Engineer who wants to join the founding team and help build the technical backbone of the company from day one.
 
 
 Tasks
 
 
 As a Founding Software Engineer, you will be responsible for designing and building the backend systems, cloud infrastructure and AI deployment architecture behind NexTex AI.
 
 
 
 You will work closely with the founders, machine learning engineers and future computer vision engineers to create a scalable edge-to-cloud platform for industrial AI applications.
 
 
 
 Your responsibilities include:
 
 
 
 &bull; Building cloud-native infrastructure and deployment pipelines
 
 
 
 &bull; Designing and developing scalable backend services and APIs
 
 
 
 &bull; Building dashboards, analytics systems and internal tools
 
 
 
 &bull; Developing industrial data pipelines for machine, sensor and camera data
 
 
 
 &bull; Supporting edge-to-cloud communication and industrial integrations
 
 
 
 &bull; Supporting AI model deployment, monitoring and inference workflows
 
 
 
 &bull; Structuring textile production data, defect classifications and sustainability KPIs
 
 
 
 &bull; Working directly with pilot factories and industrial partners
 
 
 
 &bull; Contributing to product architecture and technical strategy
 
 
 Requirements
 
 
 Strong software engineering background
 
 
 
 &bull; Strong Python and C++ programming skills
 
 
 
 &bull; Experience with FastAPI, Django, Flask, Node.js or similar frameworks
 
 
 
 &bull; Experience with PostgreSQL or similar database systems
 
 
 
 &bull; Experience with Docker and containerized environments
 
 
 
 &bull; Experience with AWS, Azure or Google Cloud
 
 
 
 &bull; Understanding of REST APIs and scalable software architectures
 
 
 
 &bull; Fluent English
 
 
 
 &bull; Ability to work independently in an early-stage startup environment
 
 
 
 Preferred Qualifications
 
 
 
 &bull; Located in Berlin or willing to relocate to Berlin
 
 
 
 &bull; Professional working proficiency in German (prior work experience in a German-speaking environment preferred)
 
 
 
 &bull; Experience with Computer Vision and Machine Learning systems (using frameworks such as PyTorch, TensorFlow or ONNX)
 
 
 
 &bull; Experience with MLOps and model deployment pipelines
 
 
 
 &bull; Experience with Edge AI deployments (NVIDIA Jetson, CUDA or TensorRT)
 
 
 
 &bull; Experience with Industrial IoT, PLC/SCADA systems or manufacturing environments
 
 
 
 &bull; Startup or founding-team experience
 
 
 
 &bull; Interest in textile manufacturing, sustainability and Industry 4.0
 
 
 Benefits
 
 
 &bull; 10% equity participation as a founding team member
 
 
 
 &bull; Approx. &euro;2,500/month through the German Federal EXIST Startup Grant during the first year
 
 
 
 &bull; Significant compensation increase planned following successful MVP validation and funding milestones
 
 
 
 &bull; Opportunity to build a deep-tech startup from day one
 
 
 
 &bull; Direct impact on product, technology and company strategy
 
 
 
 &bull; Access to real industrial production environments and pilot textile factories
 
 
 
 &bull; Work on AI, Computer Vision, Edge AI, Industrial IoT and Sustainability Intelligence
 
 
 
 &bull; Direct collaboration with experienced founders, academic advisors and industry partners
 
 
 
 &bull; Startup coaching, legal support and mentoring through EXIST and ProFIT Berlin
 
 
 
 &bull; Opportunity to shape both the product and company from an early stage
 
 
 
 &bull; Flexible working environment
 
 
 
 &bull; Potential CTO-level growth opportunities as the company scales
 
 
 
 We are looking for ambitious engineers who want to build something meaningful from the ground up. If you are excited about AI, industrial systems, sustainability and entrepreneurship, we would love to hear from you.
 
 
 
 To apply, please submit:
 
 
 
 &bull; Your CV
 
 
 
 &bull; LinkedIn profile
 
 
 
 &bull; A short introduction explaining why you are interested in joining NexTex AI
 
 
 
 Selected candidates will be invited to:
 
 
 
 1. Introductory discussion with the founders
 
 
 
 2. Technical discussion and architecture review
 
 
 
 3. Final founder meeting
 
 
 
 If successful, you will join NexTex AI as a founding team member with 10% equity and play a key role in building the future of industrial AI for textile manufacturing.
 
 
 
 We look forward to hearing from you.
 
</div>

Founding Software Engineer (Backend, Cloud & AI Infrastructure)

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