machine learning engineer

ALMEDIA

<div>This isn&rsquo;t your regular job. Almedia is a place where those who want to push harder can accelerate their careers faster than anywhere else. We&rsquo;re aiming to become Germany&rsquo;s second bootstrapped unicorn. Almedia is already Europe&rsquo;s #3 fastest-growing company in 2025 (FT1000).
We are building the future of marketing by rewarding our community of over 70 million users for engaging with our advertisers&rsquo; products. We are offering a new way to acquire users for the biggest companies in the world.<h2 class="jobSectionHeader"> 
Principal Machine Learning Engineer
</h2>You'll take ownership of the hardest ML problems across Almedia's products and growth. This is a hands-on role for someone who identifies what matters most, sets the technical direction, and drives it end to end with minimal oversight.<h2 class="jobSectionHeader">
Types of problems you'll be solving</h2><ul><li>
Designing and owning the strategy for user reward schemes at scale, across behaviour signals and market dynamics</li><li>
Architecting real-time personalisation systems for reward values that operate at production scale</li><li>
Defining how we detect and diagnose underperforming campaigns, and building the systems that act on it</li></ul><h2 class="jobSectionHeader">
Your role</h2><ul><li>
Own end-to-end delivery of high-impact ML systems: from problem framing through to production and iteration</li><li>
Set the technical bar for ML across the org, establishing best practices and raising the quality of decisions</li><li>
Define where ML creates the most business value and align the roadmap accordingly</li><li>
Apply advanced statistical and causal inference methods with rigour and production-readiness</li><li>
Partner with product and engineering leadership to shape how technical capability maps to strategic priorities</li></ul><h2 class="jobSectionHeader">
You have</h2><ul><li>
A strong track record of taking ambiguous, high-impact problems from first principles to production independently</li><li>
Deep expertise in statistics, causal inference, and experimentation at scale</li><li>
Mastery of Python and SQL, with extensive hands-on cloud and production systems experience</li><li>
A history of setting technical direction and raising the bar for engineering teams around you</li><li>
The communication range to influence both engineers and senior business stakeholders</li></ul><h2 class="jobSectionHeader">
Bonus points for</h2><ul><li>
Passion for gaming and a strong intuition for player behaviour</li><li>
Experience in adtech, monetisation platforms, or the gambling industry</li><li>
Familiarity with gaming KPIs such as pLTV, retention, and ROAS</li></ul><h2 class="jobSectionHeader">
Why Almedia?</h2><ul><li>
Scale With Almedia: Have a real impact and grow alongside a startup that has been profitable from day one.</li><li>
High-Growth Environment: We encourage all staff to take ownership of projects and consistently raise the bar.</li><li>
Do More, Get More: Generous bonus scheme to ensure great, proactive work is valued.</li></ul>
We believe in fostering talent, evaluating all skill levels during the hiring process, and providing a clear path for growth. Almedia is an equal opportunity employer. We embrace and celebrate diversity, and encourage individuals from all backgrounds to apply.</div>

Principal Machine Learning Engineer

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

Alignerr

<div>
 
 About The Role
 
 
 
 What if your machine learning expertise could directly influence how the most advanced AI systems in the world think, reason, and write code? We're looking for experienced ML engineers in Berlin to evaluate AI-generated machine learning solutions &mdash; catching errors, improving quality, and helping frontier AI models get genuinely better at one of the hardest things they do.
 
 
 This is a fully remote, flexible contract role. Work asynchronously on your own schedule. No fixed hours, no meetings &mdash; just high-impact, expert work that matters.
 
 
 <ul>
 <li>
 Organization: Alignerr
 </li>
 <li>
 Type: Hourly Contract
 </li>
 <li>
 Location: Remote (Germany-based)
 </li>
 <li>
 Commitment: Flexible, project-based
 
 
 </li>
 </ul>
 
 What You'll Do
 
 
 
 <ul>
 <li>
 Review and evaluate AI-generated machine learning code &mdash; including Python, TensorFlow, PyTorch, and scikit-learn &mdash; for correctness, efficiency, scalability, and clarity
 </li>
 <li>
 Write high-quality ML solutions to modeling, data processing, and deployment problems across a range of difficulty levels
 </li>
 <li>
 Craft clear, developer-friendly explanations for model architecture decisions, code logic, and problem-solving approaches
 </li>
 <li>
 Identify edge cases, ambiguities, and weaknesses in problem statements, datasets, or AI-generated responses
 </li>
 <li>
 Help set the quality bar for how AI understands and produces machine learning code
 
 
 </li>
 </ul>
 
 Who You Are
 
 
 
 <ul>
 <li>
 Deeply fluent in machine learning &mdash; you know your way around model development, data preprocessing, training pipelines, and deployment
 </li>
 <li>
 Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn
 </li>
 <li>
 Strong written communicator &mdash; able to explain complex ML concepts clearly and precisely in English
 </li>
 <li>
 Detail-oriented and rigorous &mdash; you catch what others miss and care about getting things right
 </li>
 <li>
 Self-motivated and comfortable working independently in an async environment
 
 
 </li>
 </ul>
 
 Nice to Have
 
 
 
 <ul>
 <li>
 3&ndash;5+ years working on machine learning projects, pipelines, or MLOps
 </li>
 <li>
 Experience with model evaluation, cloud deployment, or production ML systems
 </li>
 <li>
 Bachelor's, Master's, or PhD in Computer Science, Machine Learning, or a related field
 </li>
 <li>
 Background in data labeling, RLHF, or other AI training workflows
 </li>
 <li>
 Prior experience with code review or technical writing
 
 
 </li>
 </ul>
 
 Why Join Us
 
 
 
 <ul>
 <li>
 Work on cutting-edge AI projects alongside leading research labs and top AI teams
 </li>
 <li>
 Fully remote and async &mdash; work when and where it suits you, with no minimum hour commitments beyond project needs
 </li>
 <li>
 Freelance autonomy with the structure of meaningful, task-based work
 </li>
 <li>
 Your contributions directly improve AI models used by top research labs and enterprise teams worldwide
 </li>
 <li>
 High-performing contributors take on expanded responsibilities and lead new programs
 </li>
 <li>
 Potential for ongoing work and contract extension as new projects launch
 </li>
 </ul>
</div>

Software Engineer – Machine Learning (AI Training)

Xenon7

<div>About us:
Where elite tech talent meets world-class opportunities!
At Xenon7, we work with leading enterprises and innovative startups on exciting, cutting-edge projects that leverage the latest technologies across various domains of IT including Data, Web, Infrastructure, AI, and many others. Our expertise in IT solutions development and on-demand resources allows us to partner with clients on transformative initiatives, driving innovation and business growth. Whether it's empowering global organizations or collaborating with trailblazing startups, we are committed to delivering advanced, impactful solutions that meet today&rsquo;s most complex challenges.
We are building a community of top-tier experts and we&rsquo;re opening the doors to an exclusive group of exceptional AI &amp; ML Professionals ready to solve real-world problems and shape the future of intelligent systems.
Location: Remote (Europe - CET) 
Experience: 5+ Years
Project Duration: ~ 2 months (B2B contract) 
Availability: Immediate Joiner
Role Overview
We are seeking a visionary and highly skilled Senior Data Scientist to lead the development of a cutting-edge document intelligence and discovery platform. This unique role sits at the intersection of advanced Generative AI, Machine Learning, and Cheminformatics. Your primary mission will be to solve a highly complex unstructured data challenge: transforming scanned PDF documents containing intricate chemical structures into highly searchable, interpretable, and actionable knowledge bases.<ul><li>
Architect Document Intelligence Solutions: Design and implement advanced Machine Learning and Deep Learning models to parse, extract, and interpret text and complex chemical structures from unstructured, scanned PDF documents.</li><li>
Develop LLM &amp; Retrieval Systems: Build and optimize Large Language Model (LLM) applications, leveraging vector databases to enable semantic search, advanced data interpretation, and retrieval-augmented generation (RAG).</li><li>
End-to-End ML Pipelines: Own the entire machine learning lifecycle, including data preprocessing (specifically for chemical data and OCR outputs), model training, evaluation, deployment, and post-deployment monitoring.</li><li>
Bridge Chemistry &amp; AI: Apply your chemistry domain knowledge to translate molecular structures, diagrams, and chemical data into machine-readable formats, embeddings, and actionable insights.</li><li>
Cloud Architecture &amp; Deployment: Deploy scalable, secure, and production-ready AI/ML pipelines within the AWS ecosystem, ensuring high availability and performance.</li><li>
Cross-Functional Collaboration: Partner closely with software engineers, data engineers, and domain experts to integrate ML models into the core product architecture and align with business goals.</li></ul> 
Requirements 
<ul><li>
Professional Experience: 5+ years of proven experience working as a Data Scientist, with a track record of delivering production-grade machine learning models.</li><li>
Domain Expertise: A strong background in Chemistry, Cheminformatics, or a highly related scientific field, with a demonstrated ability to interpret and manipulate complex chemical structures and data types.</li><li>
Core Technical Stack: Advanced proficiency in Python and deep hands-on experience with the AWS cloud stack (e.g., SageMaker, Lambda, S3, EC2).</li><li>
Generative AI &amp; Search: Practical, hands-on experience working with LLMs (fine-tuning, prompt engineering, or API integration) and vector databases (e.g., Pinecone, Milvus, Weaviate, or Qdrant).</li><li>
ML/DL Mastery: Robust experience in model development, validation, deployment, and evaluation framework tools (e.g., PyTorch, TensorFlow, Scikit-Learn).</li><li>
Document Processing (Plus): Prior experience with Computer Vision, Optical Character Recognition (OCR), or Document AI systems is highly desirable given the scanned PDF focus.</li><li>
Soft Skills: Strong analytical problem-solving skills, excellent communication, and the ability to thrive in a highly collaborative, cross-disciplinary project environment.</li></ul> 

Benefits 
At Xenon7, we're not just building AI systems&mdash;we're building a community of talent with the mindset to lead, collaborate, and innovate together.<ul><li>
Ecosystem of Opportunity: You'll be part of a growing network where client engagements, thought leadership, research collaborations, and mentorship paths are interconnected. Whether you're building solutions or nurturing the next generation of talent, this is a place to scale your influence.</li><li>
Collaborative Environment: Our culture thrives on openness, continuous learning, and engineering excellence. You'll work alongside seasoned practitioners who value smart execution and shared growth.</li><li>
Flexible &amp; Impact-Driven Work: Whether you're contributing from a client project, innovation sprint, or open-source initiative, we focus on outcomes&mdash;not hours. Autonomy, ownership, and curiosity are encouraged here.</li><li>
Talent-Led Innovation: We believe communities are strongest when built around real practitioners. Our Innovation Community isn&rsquo;t just a knowledge-sharing forum&mdash;it&rsquo;s a launchpad for members to lead new projects, co-develop tools, and shape the direction of AI itself.</li></ul></div>

Senior Data Scientist - Europe

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)

Zalando

<div><div>Ort</div><div>
Germany - Berlin</div><div>
Vertrag</div><div>
Full time</div><div>
Job-Kategorie</div><div>
Applied Science &amp; Research</div></div>
 <div><div>Junior Applied Scientist (all genders) - B2B Data Science and Algorithms
The ZEOS department is responsible for all partner-facing Zalando Logistics Solutions. We provide a holistic approach to delivering the fulfillment solutions that meet our partner&rsquo;s needs by unifying these services under a single umbrella. We aim to provide our partners with a profitable fulfillment experience, and we see that to do this, Machine Learning, Operations Research, and data-driven solutions will play a pivotal role.
We are seeking a highly motivated Junior Applied Scientist who is fueled by the desire to kickstart their career by building innovative and impactful ML/Optimization systems for our B2B logistics partners. You will join an established team of Senior Applied Scientists and Machine Learning Engineers, working in a cross-functional setup with Product Managers, Data Engineers, and Software Engineers.
The team&rsquo;s focus is helping our B2B partners improve inventory health and order fulfillment efficiency. With guidance and mentorship from senior team members, you will contribute to building various ML/DL forecasting models (demand, returns, lead-times), stochastic inventory optimization solutions, recommendation services, and emerging Agentic AI systems. You will play a key role in a cross-functional team where your eagerness to learn and grow will directly translate into value for our partners!
WHY YOU SHOULD BE INTERESTED&hellip;<ul><li>
Learn and Impact from Day One: You won't be stuck doing busywork. You will be an active scientific partner, working alongside experienced scientists and product teams to define problems and build solutions. Your fresh perspective will help identify new opportunities to create value for our partners.</li><li>
Tackle Complex Scientific Problems with Expert Guidance: This is your chance to bridge the gap between academia and industry. You'll tackle cutting-edge challenges in stochastic inventory optimization, multi-echelon demand forecasting, and recommender systems while receiving the mentorship needed to succeed.</li><li>
Explore Emerging Tech like Agentic AI: As we explore opening up MCP servers to our partners, you will assist in defining how we measure their performance. You will contribute to implementing evaluation frameworks (e.g., LLM-as-a-judge, safety guardrails) to ensure autonomous systems act reliably.</li><li>
Grow into End-to-End Ownership: You will have the opportunity to follow ideas from initial research and prototyping to production. You will learn how to define success metrics, collaborate with engineers to deploy scalable services, and monitor real-world impact on partner KPIs.</li><li>
Drive Impact at a Multi-Merchant Scale: Your contributions will help build platform-level services that scale across hundreds of diverse partners, shaping the future of a more sustainable and efficient e-commerce logistics network.</li></ul> 
WE&rsquo;D LOVE TO MEET YOU IF&hellip;<ul><li>
Educational background in a quantitative field; Masters degree or higher preferred.</li><li>
Up to 2 years of hands-on experience (including internships, working student roles, or significant academic/thesis projects) applying scientific methods to solve complex problems.</li><li>
A solid theoretical foundation and practical exposure in at least one of the following areas:</li><li>
Machine Learning or Deep Learning for time-series forecasting (e.g., LGBM, ARIMA, Prophet, Transformers).</li><li>
Operations Research and Optimization (e.g., stochastic inventory models, linear/integer programming, Monte Carlo simulations).</li><li>
Machine Learning Engineering basics (e.g., understanding of git, batch processing, basic software testing).</li><li>
Agentic AI &amp; MCP evaluation frameworks</li><li>
Proficiency in SQL and Python, with some exposure to working with datasets.</li><li>
Strong communication skills with the ability to explain scientific concepts clearly and a desire to learn how to communicate effectively with business stakeholders.</li><li>
A collaborative, growth-oriented mindset. You have a passion for learning by doing and are not afraid to ask questions.</li><li>
You thrive in our team's core value: &ldquo;High Challenge, High Support&rdquo;! We cherish an open, direct feedback culture and are here to help you develop into a world-class scientist.</li></ul>
INCLUSIVE BY DESIGN
At Zalando, our vision is to be the leading pan-European ecosystem for fashion and lifestyle e-commerce - one that is inclusive by design. We only assess candidates based on qualifications, merit, and business needs. We welcome applications from people of all gender identities, sexual orientations, personal expressions, racial identities, ethnicities, religious beliefs, and disability statuses. We only want to know why you're great for this role, so please avoid including your picture, age, and marital status in your CV as well.
We want to provide you with a great candidate experience. Please feel free to inform us of any accommodations you may need, so we can best support and assist you throughout the hiring process.
do.BETTER - our diversity &amp; inclusion strategy: https://jobs.zalando.com/en/our-culture/diversity-and-inclusion
OUR OFFER<ul><li>
Zalando provides a range of benefits, here's an overview of what you can expect. Ask your Talent Acquisition Partner to learn more about what we offer.</li><li>
Employee shares program</li><li>
40% off fashion and beauty products sold and shipped by Zalando, 30% off Lounge by Zalando, discounts from external partners</li><li>
2 paid volunteering days per year</li><li>
27 days of vacation a year to start for full-time employees</li><li>
Family services, including counseling and support</li><li>
Health and wellbeing options (including Wellhub, formerly Gympass)</li><li>
Mental health support and coaching available</li><li>
Drive your development through our training platform and biannual peer-to-peer review</li></ul></div><div>
Recruiter
Casimir Udegbunam
casimir.udegbunam@zalando.de</div><div>
 Nach der Pr&uuml;fung werden unsere Recruiter*innen &uuml;ber eine offizielle Zalando E-Mail-Adresse (@zalando.de) Kontakt aufnehmen.
In einigen F&auml;llen arbeiten wir auch mit einer Auswahl von Headhunter*innen und Agenturen zusammen, um bestimmte Positionen zu besetzen. Bitte beachte, dass weder Zalando noch unsere Rekrutierungspartner*innen irgendeine Art von Bezahlung verlangen, um sich f&uuml;r eine Stelle zu bewerben oder an einem Vorstellungsgespr&auml;ch teilzunehmen.</div></div>
 <div></div><div><div><div><h2 class="jobSectionHeader">&Uuml;ber Zalando</h2>
Zalando wurde 2008 in Berlin gegr&uuml;ndet und ist die f&uuml;hrende europ&auml;ische Technologieplattform f&uuml;r Mode und Lifestyle. Wir verbinden 62 Millionen aktive Kund*innen mit mehr als 7.000 Marken in 29 M&auml;rkten. Unser Gesch&auml;ft basiert auf einer einzigartigen, KI-gest&uuml;tzten Daten- und Infrastrukturplattform. F&uuml;r unsere Kund*innen bietet unser Multi-App-Ansatz &ndash; bestehend aus Zalando, ABOUT YOU und Lounge by Zalando &ndash; ein inspirierendes, hochgradig personalisiertes Einkaufserlebnis. F&uuml;r unsere Partner bauen wir das Betriebssystem f&uuml;r den E-Commerce. &Uuml;ber ZEOS, Tradebyte und SCAYLE &ouml;ffnen wir unsere Logistik-, Software- und Servicekapazit&auml;ten f&uuml;r Marken und Einzelh&auml;ndler*innen zur nahtlosen, grenz&uuml;berschreitenden Skalierung ihres Gesch&auml;fts.</div></div></div>

Junior Applied Scientist (all genders)

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>

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