ml engineer

ista

<div>
 
 
 Hinweis: Technische St&ouml;rung bei E- Mail- Benachrichtigungen
 
 
 
 
 
 
 
 Aktuell kommt es leider zu technischen Problemen bei der Zustellung automatisierter E-Mails aus unserem Bewerbermanagementsystem. Davon betroffen sind unter anderem Eingangsbest&auml;tigungen, Zwischenbescheide und andere Benachrichtigungen. Wir arbeiten bereits an einer L&ouml;sung. Falls du keine Nachricht von uns erhalten hast oder unsicher bist, wende dich bitte direkt an die in der Stellenanzeige genannte Ansprechperson. Vielen Dank f&uuml;r dein Verst&auml;ndnis!
 
 
 
 
 
 
 
 Das erwartet dich bei uns
 
 
 
 
 
 <ul>
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 Analyse komplexer Datens&auml;tze sowie Entwicklung, Fine- Tuning und Monitoring von ML- und AI‑Modellen (inkl. Drift Detection, Log- Analysen, Classifier)
 </li>
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 Durchf&uuml;hrung statistischer Analysen und systematische Tests von ML- und LLM‑Modellen
 </li>
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 Aufbau robuster Evaluationspipelines (Validierung, Metriken, Benchmarking, Qualit&auml;tsbewertung von NLP‑Modellen)
 </li>
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 Analyse von Schwachstellen und Qualit&auml;tsabweichungen sowie iterative Optimierung der Modellperformance
 </li>
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 Entwicklung von Test‑ und Monitoring‑Frameworks f&uuml;r Modelle, Pipelines und AI‑Systeme sowie Design agentenbasierter Komponenten
 </li>
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 Zusammenarbeit mit Business‑Expert*innen beim Prompt Engineering
 </li>
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 Graph Design in Python (optional Koog) sowie Datenaufbereitung und Aufbau skalierbarer Data‑ und AI‑Pipelines
 </li>
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 Anwendung von Software‑Engineering‑Best‑Practices f&uuml;r wartbare, reproduzierbare ML‑Workflows
 </li>
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 Zusammenarbeit in cross- funktionalen Teams zur &Uuml;bersetzung von Business- Anforderungen in ML-/AI‑L&ouml;sungen und Software Engineering Teams zur &Uuml;berf&uuml;hrung von Prototypen und Evaluationen in produktive L&ouml;sungen
 </li>
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 Verst&auml;ndliche Kommunikation von Ergebnissen an technische und nicht‑technische Stakeholder
 </li>
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 Erstellung technischer Dokumentation
 </li>
 </ul>
 
 
 
 
 
 
 
 
 Das bringst du mit
 
 
 
 
 
 <ul>
 <li>
 Abgeschlossenes Studium in Informatik, Data Science, Mathematik oder einem vergleichbaren Bereich
 </li>
 <li>
 Mindestens 3 Jahre Berufserfahrung in Data Science, Machine Learning oder MLOps
 </li>
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 Erfahrung im Aufbau von Data- und ML- Pipelines
 </li>
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 Data Engineering Erfahrung ist ein Plus
 </li>
 <li>
 Fundierte Kenntnisse in Python, ML- Frameworks sowie im modernen ML-/LLM- &Ouml;kosystem (z. B. PyTorch, TensorFlow, HuggingFace, LangChain, LangGraph)
 </li>
 <li>
 Idealerweise Kenntnisse in Java
 </li>
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 Sicherer Umgang mit Software- Engineering- Best- Practices (Versionierung, Testing, CI/CD, Code- Qualit&auml;t)
 </li>
 <li>
 Erfahrung mit Cloud- Umgebungen wie Azure, AWS oder GCP
 </li>
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 Analytisches Denkverm&ouml;gen, kritisches Hinterfragen bestehender L&ouml;sungen und starke Lernbereitschaft f&uuml;r KI und neue Technologien
 </li>
 <li>
 Sehr gute Deutsch- und Englischkenntnisse
 </li>
 </ul>
 
 
 
 
 
 Das bieten wir dir
 
 
 
 
 
 <ul>
 <li>
 
 Mach das Richtige mit Sinn und Zukunft:
 
 Unsere Services sparen Co₂ und schonen die Umwelt &ndash; wir arbeiten f&uuml;r eine nachhaltige Welt von morgen
 </li>
 <li>
 
 Genie&szlig;e viele Vorteile:
 
 Freu dich auf eine attraktive Verg&uuml;tung, 30 Tage Urlaub pro Jahr sowie flexibel gestaltbare Arbeitszeiten, inkl. der M&ouml;glichkeit bis zu 50 % in der Woche mobil zu arbeiten
 </li>
 <li>
 
 Sichere dir gute Perspektiven:
 
 Wir sind ein international erfolgreiches Unternehmen mit agilen Arbeitsmethoden und einer offenen Unternehmenskultur. Unser Zukunftskurs bietet dir langfristige und hervorragende Karriereoptionen.
 </li>
 <li>
 
 Bleib neugierig und entwickle dich weiter
 
 : Stillstand ist f&uuml;r uns keine Option, deshalb f&ouml;rdern wir dich in jeder Hinsicht bei deiner Entwicklung &ndash; eine Vielzahl an Lernchancen warten auf dich
 </li>
 <li>
 
 Erlebe eine Arbeitswelt voller Vertrauen
 
 : Wir ziehen alle an einem Strang
 </li>
 <li>
 
 Hab Spa&szlig; in einem motivierten Team
 
 : Ob Grillevent, internationaler Soccer Cup oder auch mal Eis f&uuml;r alle im Sommer &ndash; wir lassen uns immer etwas Neues einfallen, sei gespannt!
 </li>
 </ul>
 
 
 
 
 
 Was machen wir bei ista?
 
 
 
 
 
 
 Wir bei ista unterst&uuml;tzen Eigent&uuml;mer:innen und Verwalter:innen von Immobilien, ihre Geb&auml;ude zukunftssicher und klimaneutral zu gestalten. Dazu geh&ouml;rt, dass wir Energieverbr&auml;uche messen, abrechnen und transparent machen. So helfen wir dabei, Energie und CO2 zu sparen. Daran arbeiten wir mit &uuml;ber 6.300 Mitarbeiter:innen in 20 L&auml;ndern. Wir bieten dir die Sicherheit eines erfolgreichen Unternehmens und die Flexibilit&auml;t einer agilen Arbeitsweise. Gestalte auch du mit uns die Zukunft.
 
 
 
 
 
 Bei ista sind alle Menschen unabh&auml;ngig von Alter, Geschlecht, Herkunft, sexueller Orientierung, Religion und Behinderung willkommen. Wir sind stolz, Teil eines vielf&auml;ltigen Teams zu sein. Wir pflegen ein kollegiales Umfeld und unterst&uuml;tzen uns gegenseitig. Besonders die Vereinbarkeit von Privatleben und Beruf hat bei uns einen hohen Stellenwert. Auch ist uns die F&ouml;rderung unserer Mitarbeiter:innen sehr wichtig, weshalb wir allen die M&ouml;glichkeit bieten, sich weiterzubilden und weiterzuentwickeln.
 
</div>

(Senior) ML/AI Engineer (m/w/d)

Lampenwelt GmbH

<div></div><div><div><h2 class="jobSectionHeader">Company description</h2>
<div>Lampenwelt has been shaping the future of lighting since 1999 with over 50,000 products, eight in-house brands, and an international team of around 500 talents. The focus is on people&rsquo;s well-being, strong customer orientation, open communication, and innovative solutions along the entire value chain, with the goal of making the world brighter and smarter.
Job description
We are building AI-powered products that directly shape how customers discover and experience lighting. As our AI Engineer, you will design, build, and take ownership of applied AI systems that create measurable business impact. 
 
This is a product-oriented engineering role, not a research position. Majority of your time will be spent on applied AI and generative systems; the remaining will support existing predictive ML models (demand forecasting, pricing, logistics). You will work closely with product managers, data engineers, and business stakeholders.
</div></div><div><h2 class="jobSectionHeader">Where your expertise is needed</h2>
<div>Applied AI &amp; Generative Systems (Primary)
<ul><li>Design and build production-ready AI systems: RAG pipelines, multi-agent orchestration, LLM-based workflow automation, and generative media applications</li>
<li>Develop evaluation frameworks that measure AI output quality, reliability and consistency</li>
<li>Design guardrails that enforce safe, predictable AI behavior in production</li>
<li>Build and maintain clean, well-documented API and service layers that integrate AI capabilities into our products</li>
<li>Collaborate with product managers to translate business problems into concrete AI solution designs</li>
<li>Stay current with the AI technology landscape and propose pragmatic improvements to our architecture</li> 
</ul>Predictive ML Support (Secondary)
<ul><li>Monitor and support existing predictive ML pipelines (regression, classification, demand forecasting, logistics)</li>
<li>Assist in detecting and triaging model drift; contribute to basic retraining or validation workflows</li>
<li>Collaborate with data engineers on feature preparation for scheduled model runs</li>
</ul></div></div><div><h2 class="jobSectionHeader">What will help you master future challenges</h2>
<div><ul><li>Applied AI engineering: Demonstrated ability to build and ship RAG systems, LLM integrations, or multi-agent workflows in production</li>
<li>Python and SQL proficiency: Comfortable writing clean, maintainable Python for production services and SQL for data retrieval and validation</li>
<li>AI evaluation: Experience designing evaluation frameworks for generative AI outputs, including metrics, test sets, and monitoring approaches</li>
<li>Production deployment: Practical experience deploying APIs or AI services to a cloud environment (any major cloud provider); understands latency, error handling, and observability basics</li>
<li>Stakeholder communication: Able to clearly communicate technical trade-offs and solution designs to non-technical collaborators; English at C1 level or above</li>
<li>ML literacy: Working understanding of supervised learning concepts (regression, classification, cross-validation) sufficient to support and interpret existing predictive models</li>
</ul></div></div><div><h2 class="jobSectionHeader">Your Benefits</h2>
<div><ul><li>A stable and engaging position in a profitable scale-up company</li>
<li>Flexible working options, from home and in one of our stylish offices in Fulda, D&uuml;sseldorf, or Berlin</li>
<li>A wide range of benefits, including free fruit and drinks, team and after-work events, and digital networking opportunities</li>
<li>A sports allowance to support your hobbies, because we care about the well-being of our team</li>
<li>Attractive employee discounts across our entire product range</li>
<li>Numerous learning and development opportunities, both within and beyond our organization</li>
</ul></div></div><div><h2 class="jobSectionHeader">Contact</h2>
<div>Melissa Barnes
jobs@lampenwelt.de
+49 661-296 962-1216 
#LI-Berlin #LI-D&uuml;sseldorf #LI-Fulda #LI-Hybrid</div></div></div>

AI Engineer (f/m/d) — Applied AI & Machine Learning

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

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>
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 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>
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 Write high-quality ML solutions to modeling, data processing, and deployment problems across a range of difficulty levels
 </li>
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 Craft clear, developer-friendly explanations for model architecture decisions, code logic, and problem-solving approaches
 </li>
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 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>
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 Strong written communicator &mdash; able to explain complex ML concepts clearly and precisely in English
 </li>
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 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>
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 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>
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 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>
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 Your contributions directly improve AI models used by top research labs and enterprise teams worldwide
 </li>
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 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)

Moss

<div>At Moss, we give finance professionals the power to automate their day-to-day and make forward-thinking decisions.
Our team and culture make us unique &mdash; we&rsquo;re driven by impact and growth, where every one of us strives to learn and excel. Recognised by Sifted&rsquo;s Rising 100 and LinkedIn's Top Startups, we&rsquo;re here to help propel your career and together, make Moss a lasting success.
We&rsquo;re expanding our Data &amp; AI team and looking for a senior/lead contributor who has hands-on LLM app/agent experience and is fluent in classical ML. You&rsquo;ll own end-to-end LLM/ML initiatives - from problem framing and modeling to evaluation, deployment, and iteration - directly improving core product workflows (invoice understanding, approval matching, reconciliation, anomaly detection, and user-assist).
Your responsibilities<ul><li>
Own LLM/ML pipelines for extraction, classification, anomaly detection, and recommendations.</li><li>
Define evaluation &amp; monitoring: gold sets, automated tests, robustness checks, SLAs, and cost/latency tracking.</li><li>
Productionize with Platform/Data Eng: bring your models live and iterate/improve until they are adopted by your stakeholders</li></ul>
About you<ul><li>
5-10+ years in applied ML with production ownership of shipping models/systems.</li><li>
Hands-on LLM app/agent experience (tool use/function calling, RAG, structured outputs, guardrails) in production.</li><li>
Strong Python + ML stack (e.g., scikit-learn, XGBoost/LightGBM, PyTorch/TF) and solid experiment/evaluation skills.</li></ul><ul><li>
Strategic Problem Solver: You approach ambiguous problems by deeply understanding business context and framing data science solutions that drive meaningful outcomes. You rigorously validate assumptions, identify root causes, and prioritize solving the right problem before building.</li><li>
End-to-End Executor: You independently own projects from ideation to production, balancing model performance with engineering realities. You ensure solutions are scalable, monitored, and maintained with thoughtful evaluation, deployment, and iteration strategies</li></ul>
About Moss
Moss is a SaaS scale-up founded in Berlin, with a team of 300+ people from 50+ nationalities in 5 offices across Europe.
Our ambition is bold: to power every SMB&rsquo;s spend across Europe - fully digital, AI-driven, and seamlessly integrated for complete control. To date, over 5000 businesses in Germany, Netherlands and the UK use Moss&rsquo; leading spend management product, with modules such as corporate cards, accounts payables, employee cash reimbursements and procurement.
Moss has raised a total of &euro;180 million in funding and is backed by the most renowned tech investors including Valar Ventures, Tiger Global, Global Founders Capital, Cherry Ventures and A-Star.
Be part of a culture that thrives on impact and speed, where you can take bold moves, learn fast and accomplish more. We&rsquo;re a place where you can fast track your career - here's what else to expect:<ul><li>
Top-of-market compensation package, including equity.</li><li>
Our vibrant offices are at the heart of our culture, where in-person time fuels collaboration and connection over weekly breakfasts and Friday demos.</li><li>
Additional benefits include: 20 days &ldquo;work from abroad&rdquo;, 600EUR/GBP Learning &amp; Development Budget, and other local benefits.</li></ul>
Unless stated otherwise, benefits apply to full-time positions (interns and working students receive a tailored package).
By applying for the above position, you will confirm that you have reviewed and agreed to our Data Privacy Policy.</div>

Senior Data Scientist (f/m/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)

ALMETRA

<div>Platform Engineer
We're looking for a (Senior) Platform Engineer to own and evolve our infrastructure &mdash; with a focus on developer experience and the chance to get hands-on with AI systems.
What you'll do<ul><li>
Design and maintain cloud infrastructure on AWS using Terraform</li><li>
Own and improve CI/CD pipelines for fast, safe deployments</li><li>
Manage and scale Kubernetes clusters</li><li>
Improve developer experience &mdash; making it easy for teams to ship and debug</li><li>
Implement monitoring, logging and alerting for full observability</li><li>
Configure and optimise CDN infrastructure</li></ul>
You are<ul><li>
8-10 years of experience in DevOps, SRE or platform engineering roles</li><li>
Expertise in AWS</li><li>
Proficient with Terraform and infrastructure-as-code workflows</li><li>
Experienced in building and maintaining CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins or similar)</li><li>
Solid understanding of Kubernetes &mdash; deployment, networking, scaling and troubleshooting</li><li>
Strong sysadmin fundamentals &mdash; Linux, networking, storage and configuration management</li><li>
Comfortable working with relational databases (PostgreSQL, MySQL) and time series databases (TimescaleDB, Prometheus)</li><li>
A clear communicator who works well across engineering and data science teams</li><li>
Pragmatic and reliable &mdash; you know when to move fast and when to be careful</li></ul>
Nice to have<ul><li>
Experience supporting ML infrastructure &mdash; model deployment, GPU workloads or training pipelines</li><li>
Background in CDN configuration (CloudFront, Fastly, Cloudflare)</li><li>
Familiarity with streaming data or video processing systems</li><li>
Interest in MLOps and bridging the gap between ML research and production</li></ul>
Why this role matters
You'll keep our systems running smoothly and help the team ship with confidence. And if you're curious about ML, you'll get real exposure to production AI systems.
#LI-SP1 #LI-Hybrid
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>
Compensation Range: &euro;70K - &euro;85K</div>

Platform Engineer (m/f/d) (AI Startup)

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