Machine Learning Engineer Jobs in Berlin, EEA

<p>We are looking for a <strong>Senior</strong> <strong>Machine Learning Engineer</strong> to join the <strong>AI Platform Team</strong> at Smartly! Our team works on helping marketers make the most of their ad creatives (images, video, text) and campaigns (product and performance data). We build and experiment with AI-based solutions across the media and creative workflows.You will have the opportunity to take ownership of and work on high impact projects.</p> <p>Join us in building high impact ML-based solutions to help our customers to build better and more effective advertising experiences for their consumers. If you’re a growth minded individual who has a passion for ML and the marketing space, this team is for you!</p> <h2><strong>As a Senior Machine Learning Engineer, you’ll:</strong></h2> <ul> <li>Build ML-based software systems that enable our users to craft great advertising experiences and campaigns </li> <li>Work with a large span of datasets from image to video to audio to text to structured performance data.</li> <li>Contribute to and strengthen Smartly’s MLOps + data platform. You’ll work alongside our stellar senior machine learning engineers, data scientists, and software engineers to enable us to productionize AI/ML applications more robustly and efficiently.</li> <li>Be a core contributor of our team and our ways of working to build high impact products. You’ll actively be involved in work planning, retrospectives, and overall team improvement.</li> <li>Impact the daily life of the staff of the hundreds of advertisers using Smartly </li> <li>Work with our stakeholders - be them product, engineering, infrastructure - to ensure we meet customers where they are. As with most ML-related roles, being able to translate business/product needs to viable solutions is a must.</li> <li>Apply and enhance your soft skills through working closely with your colleagues and our customers. Doing knowledge shares, running productive meetings, and pair programming/debugging are just some ways we grow our soft skills.</li> <li>Keep up to date with the latest ML innovations, especially in areas such as generative AI, computer vision, natural language processing and explainability.</li> </ul> <h2><strong>What we are looking for:</strong></h2> <ul> <li>5+ years of experience developing and deploying production-quality software</li> <li>2+ years of experience delivering software services powered by machine learning</li> <li>2+ years of experience working with cloud infrastructure such as AWS or GCP</li> <li>Fluent in Python; experience with C++ or Java is a plus</li> <li>Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow)</li> <li&gt

About Peregrine Based in Berlin, we're leveraging the power of AI to transform cameras into intelligent devices, enhancing road safety and urban mobility on a global scale, while preserving privacy at all times. At Peregrine, diversity and international collaboration fuel innovation. We unite the brightest minds with strong academic backgrounds and rich industry experience in robotics and machine learning, spanning from the tech hubs of Silicon Valley to the engineering powerhouses of Europe. Our team boasts alumni from leading automotive giants like Bosch, Volkswagen, IAV, and TomTom and institutions such as the ETH in Zurich. We're on the hunt for brilliant, dynamic, and passionate individuals eager to tackle challenging problems and make a tangible impact. Tasks The Role As a Senior Machine Learning Engineer, you will own the design, training, and on-device deployment of the computer vision models at the heart of our product. You will work at the intersection of research and production, turning state-of-the-art vision techniques into reliable systems that run within strict latency and privacy constraints on resource-constrained edge hardware. Your key tasks will include: Design, train, and optimize deep learning models for object detection, semantic segmentation, pose estimation, and tracking. Port and deploy models to resource-constrained edge hardware, achieving single-digit millisecond latency without cloud dependencies. Build and maintain robust vision pipelines from data ingestion through training to production inference. Apply model compression techniques such as quantization, pruning, knowledge distillation, and neural architecture search to meet strict performance budgets. Develop synthetic data and domain adaptation pipelines to close the sim-to-real gap. Profile inference pipelines end-to-end to identify and eliminate bottlenecks on target silicon. Translate cutting-edge academic research into highly reliable, production-grade systems. Collaborate closely with hardware, product, and research colleagues to shape our privacy-by-design architecture. Requirements Your Profile Core Competencies: Computer Vision & Edge AI Edge AI & On-Device Inference: Expertise in porting, deploying, and optimizing complex deep learning models for local, resource-constrained hardware without cloud dependencies. Advanced Computer Vision: Deep knowledge of developing vision pipelines for object detection, semantic segmentation, pose estimation, and tracking. Hardware-Aware Architecture Design: Ability to custom-build network topologies tailored to specific sensors and strict latency budgets, rather than relying on off-the-shelf APIs. Synthetic Data & Domain Adaptation: Proven experience in building simulation pipelines for synthetic data generation and closing the “sim-to-real” gap using Domain Randomization and GANs. Technical Stack & Tools Languages: Advanced proficiency in C++ (for production-grade edge deployment) and Python (for tra

About Wolt At Wolt, we create technology that brings joy, simplicity and earnings to the neighborhoods of the world. In 2014 we started with delivery of restaurant food. Now we're building the delivery of (almost) everything and you'll find us in over 500 cities in 30 countries around the world. In 2022 we joined forces with DoorDash and together we keep on dreaming big and expanding across the globe. Working at Wolt isn't always easy, but it's definitely exciting. Here you'll learn more, build more, and ship more than in most other companies. You'll be challenged a lot, but also have a lot of fun on the way. So, if you're a self-starter with drive and entrepreneurial spirit, this could be the ride of your life. Wolt is part of DoorDash — together we form one of the world's largest local commerce platforms, operating across DoorDash, Deliveroo, and Wolt markets in 40+ countries. Our Consumer organisation sits at the intersection of machine learning and customer experience, responsible for helping millions of customers every day find the right restaurants, dishes, and items in search, personalised recommendations, and discovery surfaces that feel intuitive and relevant. It's a domain where scale is truly global, the engineering and applied science problems are genuinely hard and scientifically interesting, and the impact on the customer experience and our business metrics is immediate and measurable. We're looking for an Applied Scientist to join our Consumer org. In this role you'll work on some of the most technically challenging ML problems across DoorDash: understanding what our customers are looking for, identifying key concepts in their queries and surfacing the most relevant results. You'll be embedded in a cross-disciplinary team of engineers, ML engineers and applied scientists with full ownership from research to production. If your expertise matches our domain and you want to work on hard problems at global scale alongside exceptional colleagues, we'd love to meet you. What you'll be doing As an Applied Scientist in Consumer, you'll advance the ML models and methods that power how customers across DoorDash, Deliveroo, and Wolt find and discover content. You'll work end-to-end collaborating closely with engineers and product managers to deliver real impact. Day-to-day in this role you'll: Design and develop ML models for search relevance, query understanding, and ranking that operate across DoorDash, Deliveroo, and Wolt's 40+ markets. Bring state-of-the-art solutions to our stack for the delight of our customers, helping the team to impact business metrics. Work end-to-end on ML problems: from problem framing and data analysis through model development, offline evaluation, and production monitoring. Collaborate with Software Engineers, ML Engineers, Product Managers, and Analysts to translate research insights into real customer impact. Contribute to our group-wide Applied Science community through knowledge sharing, technical revie

About the team: Within the Global Operations organisation, our mission is to build the best customer experience in the fintech industry by delivering an effortless customer experience to all our merchants. We are seeking a skilled and passionate Senior AI / Machine Learning Engineer to join our talented AI team and lead the development of AI models and algorithms that will drive our customer support service to new heights. As a Senior AI / Machine Learning Engineer at SumUp, you will be responsible for building and optimizing state-of-the-art AI models and algorithms. Your expertise with machine learning, deep learning, and LLMs will be crucial in driving the success of our AI-driven initiatives. You will work closely with cross-functional teams, including backend engineers, data scientists and product managers, to translate business requirements into innovative AI solutions. Your contributions will shape the future of our support products and help us stay at the forefront of technological advancements in the field of AI. What you'll do Architect, design, develop and deploy our AI solutions and systems in production environments, ensuring reliability, high performance and scalability. Collaborate and communicate closely with data scientists, product managers, developers and other business stakeholders to bring state-of-the-art AI solutions to Customer Support, enhancing customer experience and improving operational efficiency. Develop and maintain ML infrastructure and pipelines to support efficient data processing, model training and serving. Optimize and fine-tune machine learning models to improve accuracy, efficiency and scalability. Collect, preprocess and clean large text datasets to ensure high-quality input for model training and evaluation. Embrace software development principles, best practices and industry standards, including version control, CI/CD processes and unit testing frameworks as your day-to-day work. Collaborate with cross-functional teams to ensure seamless integration of machine learning solutions into software applications and platforms.  You'll be great for this position if you have: Bachelor's degree in Machine Learning, Computer Science or an engineering-related field. +8 years of proven experience working as a Machine Learning Engineer, focusing on building and deploying scalable machine learning or AI solutions and data-driven systems. Relevant experience building AI products, such as Chatbot Assistant, RAG system, etc. Excellent software development engineering skills to design computationally effective solutions and maintenance in large-scale production environments (data version control, model serving, continuous monitoring & alerting) Experience building and deploying ML models using cloud services (AWS, GCP, or Azure). Expert in Python and familiarity with MLOps tools (e.g., MLflow, Kubeflow, Airflow, Langfuse). Experience with machine learning workflow orchestration and algorithms optimisation, feature

At SumUp, we are motivated by the purpose of levelling the playing field for small businesses. We empower small business owners by creating simple and affordable tools to manage payments, finance and customer relationships. We are a passionate team that thrives on human connection, autonomy and the desire to constantly learn, guided by our values: Founder's Mentality, Team First, and We Care. We want to build an enduring organisation that is people-positive, disciplined and that constantly innovates from within. Agility is the essence of an enduring organisation and we strive to create an organisation that fosters it. In Global Operations, we build the best customer experience in fintech. The Senior AI/ML Engineer role is critical for developing and deploying the next generation of AI-driven solutions that automate support and drastically improve the experience for both our merchants and support agents. You will be a key expert who builds and maintains the ML infrastructure and tooling that powers our core products using advanced AI/ML models. This role is a replacement, essential for maintaining momentum as we expand complex use cases like our AI Assistant and translation tools. What You'll Be Doing You will be the dedicated technical leader for the Operations AI team, focused on designing, developing, and deploying high-performance, scalable ML/AI solutions in production environments. Architect, design, develop, and deploy our AI solutions and systems into production environments, ensuring reliability, high performance, and scalability. Take ownership and technical leadership in the development and maintenance of main AI products, including the AI Assistant (automating ~40% of merchant requests), AI Translation (enabling cross-language agent service), and the AI Agent Copilot. Develop and maintain ML infrastructure and pipelines to support efficient data processing, model training, serving, and continuous monitoring. Optimise and fine-tune machine learning models, and collect, preprocess, and clean large text datasets to ensure high-quality input for model training and evaluation. Embrace software development principles, best practices, and industry standards, including version control (Git), CI/CD processes (GitHub actions), and unit testing frameworks. Collaborate closely with Data Scientists, Product Managers, Developers, and other business stakeholders to enhance customer experience and improve operational efficiency globally. Complex Onboarding: Rapidly master a large, existing AI assistant infrastructure, starting immediately with working on behaviour improvements and agentic rollouts. Pilot and Innovation: Lead the creation of the pilot for the Voice Assistant and design how to leverage current AI assistant components to empower new channels. You'll Be Great for This Position If You Have 7+ years of proven experience as a Machine Learning Engineer or AI Engineer, focusing on building and deploying scalable machine learning or AI solution

Machine Learning Engineer at Almedia. Apply via Ashby.

Senior Machine Learning Engineer at Payrails. Apply via Ashby.

Vestiaire Collective is the leading global online marketplace for desirable pre-loved fashion. Our mission is to transform the fashion industry for a more sustainable future by empowering our community to promote the circular fashion movement. Vestiaire was founded in 2009 and is headquartered in Paris with offices in London, Berlin, New York, Singapore, Ho Chi Minh, and warehouses in Tourcoing (France), Crawley (UK), Hong Kong and New York. We currently have a diverse global team of 600 employees representing more than 50 nationalities. Our values are Activism, Transparency, Dedication and Greatness and Collective. About the Role We are seeking a Foundational Machine Learning Engineer for a high-impact greenfield opportunity to build our MLOps infrastructure from the ground up at Vestiaire Collective. While driving our AI authentication initiatives (deploying multi-model approaches including computer vision for luxury product authentication and counterfeit detection) will be your immediate focus, your long-term mission will be to scale foundational architecture across the entire marketplace. You will expand our ML capabilities to power broader domains, primarily focusing on search and recommendation systems, with future expansions into dynamic pricing and marketing technologies. Acting as the bridge among Applied Science, Data Platform, and Backend Engineering, you will design robust, decoupled architectures and spearhead the MLOps strategy with our Director of Data, prioritizing system maintainability, engineering hygiene, and the reliable deployment of complex models, ensuring all our ML models across the board deliver high-throughput, low-latency business impact. What You Will Do Short-Term Impact (First 6 Months): Partner closely with the Operations squads and Data Scientists to accelerate ML and RAG prototypes into resilient, production-ready code. You will directly integrate with the team to deploy, optimize, and scale heavy-width CV and VLM models focused on fraud detection and luxury product authentication, immediately improving our trust and safety ecosystem. Mid-Term Foundation (MLOps Lifecycle & Infrastructure): Lead the end-to-end foundational groundwork of our ML lifecycle by designing robust systems for Data & Feature Management, Model Tracking & Registry, and Model Serving & Monitoring. You will scale infrastructure by automating continuous retraining pipelines that handle diverse deployment cadences (from daily fraud detection to weekly recommendations), design resilient multi-model architectures, and critically evaluate the technical overhead and TCO of our in-house tools against enterprise-grade platforms to ensure long-term resilience. Long-Term Vision (Centralizing 360-Degree MLE Capabilities): Act as a pioneer and cornerstone hire for the ML engineering discipline at Vestiaire Collective, setting the technical standards to help scale the AI/ML organization. You will transition into a centralized foundational role, moving beyond single-squad operations to mentor the team and provide horizontal ML infrastructure support to multiple domains, including Search, Discovery, Pricing, Marketing, and Data Platforms. Who You Are Must-Haves: Experience: 5-8+ years of hands-on experience in Machine Learning Engineering, specifically focused on building and scaling MLOps infrastructure and productionizing ML systems. Production Infrastructure: Proven expertise in deploying low-latency, high-throughput ML inference services (using FastAPI, TorchServe, Triton Inference Server, or Ray Serve) across both classical lightweight and heavy-width ML models (PyTorch/TensorFlow). Strong preference for AWS (EKS, EC2, SageMaker) / Snowflake and Open Source ecosystems over GCP/Azure. MLOps & Pipelines: Deep experience building automated, continuous model retraining pipelines to handle concept drift (ranging from daily to weekly cycles). You have orchestrated decoupled, multi-model AI architectures using tools like Airflow, Kubeflow, or Metaflow, and possess strong expertise in model registry and tracking tools like MLflow or Weights & Biases. Feature Stores: Hands-on experience evaluating, building, or extensively leveraging online (Redis, DynamoDB) and offline (Snowflake, S3) Feature Stores in a production environment. Familiarity with frameworks like Feast or custom dbt-based pipelines is highly valued. Strategic Builder Mindset: You are an analytical builder who thinks long-term. You can successfully evaluate TCO for bespoke internal systems versus enterprise tools, anticipate technical liabilities, and design robust architectures that handle unpredictable peak traffic surges. Collaboration & Engineering Hygiene: Strong cross-functional communication skills. You excel at translating complex ML prototypes into highly scalable production code backed by strict version control, rigorous testing, and CI/CD best practices, seamlessly connecting data science innovation with backend engineering execution. Nice-to-Haves: Relevant Domain Expertise: Background in E-commerce, Single-SKU Marketplaces, Search & Recommendation, Trust & Safety, or Counterfeit Detection. Vision, Edge & Optimization: Hands-on experience with Vector Databases, Visual RAG pipelines, deploying Deep Learning VLM models, and optimizing models for edge computing or low-latency inference (e.g., ONNX, TensorRT). Infrastructure & Observability: Advanced experience with containerization (Docker, Kubernetes), Infrastructure as Code (Terraform), and data transformation workflows (dbt). Familiarity with setting up advanced monitoring for model performance, concept drift, and system health (Datadog, Prometheus).

Veeva Systems is a mission-driven organization and pioneer in industry cloud, helping life sciences companies bring therapies to patients faster. As one of the fastest-growing SaaS companies in history, we surpassed $3B in revenue in our last fiscal year with extensive growth potential ahead.   At the heart of Veeva are our values: Do the Right Thing, Customer Success, Employee Success, and Speed. We're not just any public company – we made history in 2021 by becoming a public benefit corporation (PBC), legally bound to balancing the interests of customers, employees, society, and investors.   As a Work Anywhere company, we support your flexibility to work from home or in the office, so you can thrive in your ideal environment.   Join us in transforming the life sciences industry, committed to making a positive impact on its customers, employees, and communities. The Role Veeva Data Cloud is connected data for Life Sciences to accelerate insights and increase efficiency with better data built on a common data architecture. Within Data Cloud we are the AI team powering the entire suite of products. By building a unified set of AI tools, we enable agility and quality at a global scale. Our state-of-the-art ML and AI models complement the work of more than  3000 data stewards and thereby re-inforce each other. By combining AI with human data stewards, we are able to transform data into actionable insights so that clinical innovation can be developed faster and ultimately more patients can access the treatments they need. We are looking for someone to work in a cross-functional team of data scientists, engineers and data product managers to productize and scale the AI tools that we build. Veeva is a work-anywhere company which means you can work in an office or at home on any given day. It’s about getting the work done in the way and place that works best for each person.

<gh-intro> <text> We are looking for a Staff Machine Learning Engineer, AI Applications to join Bolt's Customer Support Product team and lead the quality, learning, and knowledge foundations behind our AI automation stack. You will have the opportunity to shape how we evaluate and align LLM-based systems, improve knowledge quality and retrieval, and build the feedback loops that continuously improve customer support automation. If you are passionate about applied ML, retrieval and knowledge systems, and making AI products measurably better in production, this role will perfectly suit you. </text> </gh-intro> <gh-about-us> <title> About us </title> <text> With over 200 million customers in 50+ countries, Bolt is one of the fastest-growing tech companies in Europe and Africa. And it's all thanks to our people. We believe in creating an inclusive environment where everyone is welcome, regardless of race, colour, religion, gender identity, sexual orientation, national origin, age, or disability. Our ultimate goal is to make cities for people, not cars, and we need your help to achieve this mission! </text> </gh-about-us> <gh-role-detail> <title> About the role </title> <text> As a Staff Machine Learning Engineer, you will operate at the intersection of advanced AI, knowledge systems, and Bolt's production support ecosystem, setting the technical direction for how we measure, improve, and scale AI quality across conversational experiences. You will help ensure our systems are accurate, helpful, grounded, and aligned with business and customer needs. This is a high-impact, high-scope role where you will define the quality and learning strategy behind our AI systems, partner closely with engineering, product, operations, and domain experts, and turn real-world support interactions into durable improvements across models, retrieval, and workflows. You will work closely with engineers and cross-functional partners building Bolt's AI automation stack, helping ensure our systems are not only scalable and reliable, but also grounded, aligned, and continuously improving in production. </text> </gh-role-detail>   <gh-responsibilities> <title> Main tasks and responsibilities: </title> <bulletpoints> <point>Lead alignment of Customer Support AI system behaviour to Bolt's business goals, customer experience standards, and policy requirements, improving answer quality, consistency, grounding, and escalation behaviour..</point> <point>Build and scale knowledge mining capabilities that turn conversations, support tickets, workflows, policies, and operational data into reusable knowledge assets and improvement signals .</point> <point>Own the evaluation strategy for LLM-powered customer support systems, including offline benchmarks, golden datasets, human review workflows, online experimentation, and production qua

Founding Computer Vision Engineer (Up to 15% Equity + EXIST Funding) INTRO NexTex AI is building machine-level intelligence for textile manufacturing. Our platform combines industrial cameras, retrofit sensors, machine data, and AI models to detect textile defects, identify production anomalies, and generate sustainability intelligence across knitting, dyeing, finishing, and quality control operations. Unlike traditional quality control systems, NexTex AI connects machine behavior, fabric quality, and sustainability performance through a unified industrial AI platform. By combining computer vision, machine signals, production metadata, and process parameters, we help manufacturers reduce fabric waste, rework, water consumption, energy usage, and CO₂ emissions while improving process stability and production quality. Initial applications include needle-related defects, elastane failures, oil stains, fabric distortions, shade deviations (ΔE), machine start-stop anomalies, and process instabilities in large-scale textile production environments. NexTex AI is currently preparing its EXIST startup funding application and collaborates with industrial partners including Terrot Textilmaschinen GmbH in Germany, as well as Ribana Tekstil and Nuryıldız Tekstil in Turkey. These partnerships provide direct access to real production environments, industrial machine fleets, textile defect scenarios, and manufacturing datasets. We are looking for a Founding Computer Vision Engineer to join the core team and help build the AI technology behind NexTex AI from the ground up. Tasks Tasks • Design, develop, and deploy computer vision systems for industrial textile inspection • Build object detection, segmentation, classification, and anomaly detection models using real-world manufacturing data • Train, evaluate, and optimize deep learning models using modern computer vision architectures • Develop image acquisition, preprocessing, augmentation, labeling, and validation pipelines • Build and maintain large-scale industrial image and video datasets collected from textile production environments • Develop multimodal AI systems combining visual data, machine events, sensor signals, PLC/SCADA data, and production metadata • Optimize models for edge deployment and real-time inference in industrial environments • Develop model monitoring, validation, and continuous learning workflows • Work directly with real-world manufacturing challenges including needle-related defects, elastane failures, oil stains, fabric distortions, shade deviations (ΔE), and machine-process anomalies • Collaborate with textile engineers and industrial partners to translate manufacturing problems into scalable AI solutions • Contribute to the architecture of NexTex AI’s edge-to-cloud industrial AI platform • Participate in pilot deployments and industrial validation projects with textile manufacturers and machine technology partners • Help define the long-term AI strategy, technical roadmap, dataset

<gh-intro> <text> We are looking for a Staff Machine Learning Engineer, AI Applications to join Bolt's Customer Support Product team and lead the quality, learning, and knowledge foundations behind our AI automation stack. You will have the opportunity to shape how we evaluate and align LLM-based systems, improve knowledge quality and retrieval, and build the feedback loops that continuously improve customer support automation. If you are passionate about applied ML, retrieval and knowledge systems, and making AI products measurably better in production, this role will perfectly suit you. </text> </gh-intro> <gh-about-us> <title> About us </title> <text> With over 200 million customers in 50+ countries, Bolt is one of the fastest-growing tech companies in Europe and Africa. And it's all thanks to our people. We believe in creating an inclusive environment where everyone is welcome, regardless of race, colour, religion, gender identity, sexual orientation, national origin, age, or disability. Our ultimate goal is to make cities for people, not cars, and we need your help to achieve this mission! </text> </gh-about-us> <gh-role-detail> <title> About the role </title> <text> As a Staff Machine Learning Engineer, you will operate at the intersection of advanced AI, knowledge systems, and Bolt's production support ecosystem, setting the technical direction for how we measure, improve, and scale AI quality across conversational experiences. You will help ensure our systems are accurate, helpful, grounded, and aligned with business and customer needs. This is a high-impact, high-scope role where you will define the quality and learning strategy behind our AI systems, partner closely with engineering, product, operations, and domain experts, and turn real-world support interactions into durable improvements across models, retrieval, and workflows. You will work closely with engineers and cross-functional partners building Bolt's AI automation stack, helping ensure our systems are not only scalable and reliable, but also grounded, aligned, and continuously improving in production. </text> </gh-role-detail>   <gh-responsibilities> <title> Main tasks and responsibilities: </title> <bulletpoints> <point>Lead alignment of Customer Support AI system behaviour to Bolt's business goals, customer experience standards, and policy requirements, improving answer quality, consistency, grounding, and escalation behaviour..</point> <point>Build and scale knowledge mining capabilities that turn conversations, support tickets, workflows, policies, and operational data into reusable knowledge assets and improvement signals .</point> <point>Own the evaluation strategy for LLM-powered customer support systems, including offline benchmarks, golden datasets, human review workflows, online experimentation, and production qua

About Wolt At Wolt, we create technology that brings joy, simplicity and earnings to the neighborhoods of the world. In 2014 we started with delivery of restaurant food. Now we're building the delivery of (almost) everything and you'll find us in over 500 cities in 30 countries around the world. In 2022 we joined forces with DoorDash and together we keep on dreaming big and expanding across the globe. Working at Wolt isn't always easy, but it's definitely exciting. Here you'll learn more, build more, and ship more than in most other companies. You'll be challenged a lot, but also have a lot of fun on the way. So, if you're a self-starter with drive and entrepreneurial spirit, this could be the ride of your life. Wolt's Personalization team is responsible for creating a tailored experience for Wolt's customers across their shopping journey, selecting the best restaurants, dishes or items to match their culinary and shopping preferences across multiple premises such as Discovery, In Venue or Checkout. The Personalization team owns the ML stack, models and integrations that generate real-time recommendations for millions of customers across all Wolt markets. For example, the team is responsible for the models that rank restaurants in Wolt's Discovery and Restaurants tabs, venues in Wolt's Discovery and Stores tabs or items in Wolt's in-venue and cart premises. It also personalises other components in Wolt's shopping experience such as brands, banners or food categories that are relevant entry points for our customers to explore Wolt's assortment. As a Machine Learning (ML) Engineer in Wolt's Personalization team you will: Build the ML infrastructure to develop, train and deploy Wolt's ranking models that select the content to display to our customers; Work end-to-end, from use case design to implementation, delivery and monitoring of your solutions; Maintain our production ML stack and raise the team's ML engineering excellence bar; Liaise with Wolt's ML Platform team to adopt different ML technologies and to create technical requirements for their solutions; Contribute to Wolt ML Engineering and Applied Science communities; Be part of a cross-disciplinary team with Applied Scientists, Software Engineers and Analysts to provide solutions to customer problems with a direct impact on the company's business KPIs; Work at Wolt's scale: Wolt operates in 30 different markets with millions of customers. 📍This role can be based in one of our tech hubs in Berlin, Helsinki, or Stockholm, or you can work remotely anywhere in Finland, Sweden, Germany.  Read more about our remote setup here .  Qualifications You are experienced in end-to-end machine learning deployments and maintenance of ML systems and have at least 2+ years of experience in ML/MLOps; You have deployed and ran ML models in production at scale, maybe with hundreds of RPS and low latency; You bring solid experience in scaling solutions, monitoring ML stacks and troubleshooting ML deplo

Doopic ist ein innovatives Unternehmen aus Berlin, das sich auf das Thema Produktbildbearbeitung und Postproduktion spezialisiert hat. Mit starkem Fokus auf revolutionären Workflows, Automationen und KI nehmen wir eCommerce-Betreibern, Fotostudios, uvm. die Fleißarbeit hinsichtlich der Bildbearbeitung ab und unterstützen sie mit weiteren grafischen Dienstleistungen und einem hervorragenden Kundenservice. Zum nächstenmöglichen Zeitpunkt freuen wir uns auf Dich als AI Media Engineer (m/w/d) in unserem Office am Kurfürstendamm in Berlin. Wir suchen nach Personen mit Wohnsitz in Berlin. Aufgaben Du entwickelst, trainierst und optimierst Machine-Learning-Modelle im Bereich Computer Vision und Generative AI (z. B. Diffusion, Segmentierung, Bildverarbeitung). Du integrierst ML-Modelle in bestehende Produktions-Workflows und sorgst für stabile, skalierbare Prozesse im Alltag. Du arbeitest an der Automatisierung unserer Bildbearbeitungsprozesse und reduzierst manuelle Arbeit durch innovative Ansätze. Du analysierst die Performance unserer Modelle, identifizierst Schwachstellen und verbesserst kontinuierlich Qualität und Robustheit. Du arbeitest eng mit Produktentwicklung, Engineering und Operations zusammen, um ML-Lösungen praxisnah umzusetzen. Du analysierst neue Technologien und Ansätze im Bereich AI und bringst diese schnell in die Anwendung. Qualifikation Mehrjährige praktische Erfahrung im Bereich Machine Learning / Computer Vision. Analytisches Denken, pragmatische Herangehensweise und Hands-on-Mentalität. Gute Kenntnisse in Python (Frameworks wie PyTorch oder TensorFlow). Praktische Erfahrung mit generativen Modellen (z. B. Diffusion Models, GANs) Verständnis für produktionsnahe ML-Systeme (Deployment, Skalierung, Performance). Erfahrung mit produktionsnahen Tools und Workflows (z. B. Docker, AWS/Azure). Erfahrung mit kreativen AI-Workflows und Tools wie ComfyUI oder Photoshop. Erfahrung im Bereich Produktfotografie und E-Commerce wünschenswert Gute Deutsch- und Englischkenntnisse. Benefits Bei uns bringt jeder Tag neue, spannende Herausforderungen, die wir gemeinsam angehen. Hier schaut Dir bei der Arbeit niemand prüfend über die Schulter. Was zählt, sind die Ergebnisse und die sind bei uns (fast) immer grandios – schon alleine, weil wir mit so viel Spaß bei der Sache sind. Team Events, kostenlose Snacks, Obst, Kaffee etc. sind selbstverständlich Standard. Wir arbeiten mit den besten Tools, Materialien und Kollegen an einem attraktiven Standort im Herzen Berlins mit sehr guter Verkehrsanbindung - Das Jobticket wird bezuschusst Wir arbeiten mit den besten Tools, Materialien und Kollegen, bieten flexible Arbeitszeiten, die Möglichkeit auf Homeoffice und natürlich ein kompetitives Gehalt. Nicht zuletzt liegt uns daran Dich jeden Tag etwas besser zu machen und deswegen spendieren gerne Seminare und Fortbildungen Sollte die Anzeige Dein Interesse geweckt haben, dann schicke uns gerne Deine Bewerbung mit Deinem Lebenslauf, dem frühestmöglichen Startterm