[{"_1":2,"_76":-5,"_77":-5},"loaderData",{"_3":4,"_9":10},"root",{"_5":6,"_7":8},"url","http://nextleveljobs.eu/companies/miro/de","savedJobIds",[],"routes/companies_.$companyId.$countryCode",{"_11":12,"_13":14,"_15":16,"_74":75},"company","Miro","countryName","Germany","jobs",[17,63],{"_18":19,"_11":20,"_21":22,"_23":24,"_25":26,"_27":-5,"_28":29,"_30":31,"_32":33,"_34":35,"_36":-5,"_37":38,"_39":40,"_41":40,"_42":43,"_44":45,"_46":47,"_48":47,"_49":47,"_50":22,"_51":47,"_52":40,"_53":54,"_55":56,"_57":47,"_58":59,"_60":61},"id","698ca397d4ff3539125a5ac7","miro","remoteId","Miro-8395670002","title","Lead Research Scientist","link","https://miro.com/careers/vacancy/8395670002?gh_jid=8395670002","keywords","created",1770824599,"found",0,"lastSeen",1773932257,"location","Copenhagen, DK; London, UK; Remote EMEA","locations","locationId","000000000000000000000000","remote",true,"allRemote","description","<h4></h4>Miro is looking for a Lead Research Scientist to serve as the technical "North Star" for our Machine Learning organization. You will operate as a high-level Individual Contributor (Staff/Principal level), driving the architectural decisions behind the "Intelligent Canvas."Your challenge is unique in the industry: You are not just processing text. You are building models that understand spatial relationships, visual diagrams, and unstructured collaboration. You will research, prototype, and ship novel architectures that combine Large Language Models (LLMs), Computer Vision, and Graph Neural Networks (GNNs) to make Miro the smartest collaboration platform on earth.<h4>What you’ll do</h4><ul><li>Pioneer Novel Architectures: Move beyond off-the-shelf APIs. You will design and train custom architectures that fuse multimodal inputs (text, sketches, diagrams, screenshots, code, etc.) into a unified representation of user intent.</li><li>Bridge Theory and Production: You will read the latest papers (NeurIPS, ICLR, CVPR) on Monday and have a working prototype by Friday. You bridge the gap between academic theory and scalable, low-latency production systems.</li><li>Define the Technical Strategy: While Managers define what we build, you define how we build it. You will make high-stakes decisions on model selection (e.g., Diffusion vs. Autoregressive), build vs. buy, and fine-tuning strategies (LoRA, Q-LoRA).</li><li>Mentorship & Technical Excellence: You will elevate the entire ML research engineering organization by conducting rigorous code reviews, hosting paper reading groups, and mentoring research engineers on mathematical fundamentals and experimental design.</li><li>Solve the "Unsolved": You will tackle ambiguous problems with no StackOverflow answers—such as "How do we generate a valid UML diagram from a rough sticky-note brain dump?" or "How do we detect 'agreement' in a spatial cluster of comments?"</li></ul><h4>What you’ll need</h4><ul><li>Deep Research Expertise: PhD or equivalent deep industrial experience in Computer Science, Math, or Physics. You have a track record of publishing in top-tier conferences or shipping models that serve millions of users.</li><li>Public Track Record: A portfolio of patents, impactful open-source contributions, or first-author publications in top-tier conferences (NeurIPS, ICML, CVPR, ICLR).</li><li>Mastery of the Modern Stack: You are an expert in PyTorch or JAX. You can implement complex loss functions from scratch and debug distributed training issues on massive GPU clusters.</li><li>Specialization in Structure & Generation: Deep experience in at least one of the following: Generative AI (LLMs/Diffusion), Graph Neural Networks (GNNs), or Geometric Deep Learning. You understand how to model relationships, not just tokens.</li><li>Engineering Rigor: You write clean, modular, production-ready code. You understand the trade-offs between model accuracy and inference latency.</li><li>Communication: You can explain the "Why" behind complex mathematical concepts to Product Managers, Designers, and Executives, turning abstract research into a compelling product vision.</li></ul>Education + Experience<ul><li>Option A: PhD in Computer Science, Machine Learning, Mathematics, Physics, or related field plus 4+ years of professional experience shipping ML at scale.</li><li>Option B: Master’s degree or equivalent deep technical experience plus 7+ years of industry experience, with at least 2 years operating at a Senior or Staff level (driving technical strategy).</li></ul>Bonus (Nice-to-Have)<ul><li>Graph Learning Expertise: Specific experience with Graph Neural Networks (GNNs) or Geometric Deep Learning. You understand how to apply ML to non-Euclidean data (like the node-edge relationships on a Miro canvas).</li><li>Generative Media: Hands-on experience building or fine-tuning Diffusion models for image/video generation or Multimodal LLMs (vision + text).</li><li>Performance Optimization: Experience porting models to constrained environments (e.g., ONNX, WebGpu, CoreML) or optimizing inference for real-time interaction in the browser.</li><li>Domain Knowledge: Previous work in Computational Creativity, HCI (Human-Computer Interaction), or building tools for thought (e.g., knowledge graphs, whiteboarding tools).</li></ul><h4>What's in it for you</h4>We want you to feel supported, connected, and ready to grow. Our global benefits package generally includes equity, a wellbeing benefit, a WFH equipment allowance, and an annual Learning & Development stipend. Join a diverse team where you can do your best work. Full benefits may differ per location. If you would like to learn more about location-specific benefits, please refer to our <a href="https://miro.com/app/board/uXjVG8Fi8Yc=/?moveToWidget=3458764661021134968&cot=10" target="_blank">Global Miro benefits board.</a>Recruiter: #LI-MH1<div class="content-conclusion"><h4>About Miro</h4>\nMiro is a visual workspace for innovation that enables distributed teams of any size to build the next big thing. The platform's infinite canvas enables teams to lead engaging workshops and meetings, design products, brainstorm ideas, and more. Miro, co-headquartered in San Francisco and Amsterdam, serves more than 100M users and 250,000 companies collaborate in the Innovation Workspace. Miro was founded in 2011 and currently has more than 1,600 employees in 13 hubs around the world.\nWe are a team of dreamers. We look for individuals who dream big, work hard, and above all stay humble. Collaboration is at the heart of what we do and through our work together we hope to create a supportive, welcoming, and innovative environment. We strive to play as a team to win the world and create a better version of ourselves every day. If this sounds like something that excites you, we want to hear from you!\nCheck out more about life at Miro: \n<ul class="p-rich_text_list p-rich_text_list__bullet" data-stringify-type="unordered-list" data-indent="0" data-border="0">\n<li data-stringify-indent="0" data-stringify-border="0">Youtube: <a class="c-link" href="https://www.youtube.com/@lifeatmiro" target="_blank" data-stringify-link="https://www.youtube.com/@lifeatmiro" data-sk="tooltip_parent">https://www.youtube.com/@lifeatmiro</a></li>\n<li data-stringify-indent="0" data-stringify-border="0">Blog: <a class="c-link" href="https://miro.com/careers/life-at-miro/all/" target="_blank" data-stringify-link="https://miro.com/careers/life-at-miro/all/" data-sk="tooltip_parent">https://miro.com/careers/life-at-miro/all/</a></li>\n<li data-stringify-indent="0" data-stringify-border="0">Instagram: <a href="https://www.instagram.com/mirohq/">https://www.instagram.com/mirohq/</a></li>\n</ul>\n<hr>\nAt Miro, we strive to create and foster an environment of belonging and collaboration across cultural differences. Miro’s mission — Empower teams to create the next big thing — is how we think about our product, people, and culture. We believe that creating big things requires diverse and inclusive teams. Diversity invites all talent with different demography, identities and styles to step in, and inclusion invites them to step closer together. Every day, we are working to build a more diverse Miro, cultivate a sense of belonging for future and current Mironeers around the world, and foster an environment where everyone can collaborate and embrace differences.\nMiro handles and uses personal data of job applicants in line with its <a href="https://miro.com/legal/recruitment-privacy-policy/" target="_blank">Recruitment Privacy Policy</a> found <a href="https://miro.com/legal/recruitment-privacy-policy/" target="_blank">here</a>. </div>","seniorityLevel","staff","salary","","countryCode","city","companyRemoteId","cookieId","indexed","unindexed",false,"aiDescription","

Requirements

Deep Research Expertise: PhD or equivalent deep industrial experience in Computer Science, Math, or Physics.
Public Track Record: A portfolio of patents, impactful open-source contributions, or first-author publications in top-tier conferences.
Mastery of the Modern Stack: Expert in PyTorch or JAX.
Specialization in Structure & Generation: Deep experience in Generative AI, Graph Neural Networks, or Geometric Deep Learning.
Engineering Rigor: Write clean, modular, production-ready code.
Communication: Ability to explain complex mathematical concepts to various stakeholders.

\n\n

Nice-to-Haves

Graph Learning Expertise: Experience with Graph Neural Networks or Geometric Deep Learning.
Generative Media: Hands-on experience with Diffusion models or Multimodal LLMs.
Performance Optimization: Experience in porting models to constrained environments or optimizing inference for real-time interaction.
Domain Knowledge: Previous work in Computational Creativity, HCI, or building tools for thought.

\n\n

What You'll Be Doing

Pioneer Novel Architectures: Design and train custom architectures that fuse multimodal inputs.
Bridge Theory and Production: Translate academic theory into scalable production systems.
Define the Technical Strategy: Make critical decisions on model selection and strategies.
Mentorship & Technical Excellence: Elevate the ML research engineering organization through mentorship.
Solve the \"Unsolved\": Tackle ambiguous problems creatively.

\n\n

Perks and Benefits

Competitive equity package
Health insurance for you and your family
Corporate pension plan
Lunch, snacks, and drinks provided in the office
Wellbeing benefit and WFH equipment allowance
Annual learning and development allowance
Opportunity to work for a globally diverse team

","category","stack","machinelearning","techStack",[62],"nodejs",{"_18":64,"_11":20,"_21":65,"_23":66,"_25":67,"_27":-5,"_28":68,"_30":31,"_32":33,"_34":35,"_36":-5,"_37":38,"_39":40,"_41":40,"_42":69,"_44":70,"_46":47,"_48":47,"_49":47,"_50":65,"_51":47,"_52":40,"_53":54,"_55":71,"_57":47,"_58":59,"_60":72},"698c8777d4ff3539125a5a9a","Miro-8395672002","Machine Learning Research Engineer","https://miro.com/careers/vacancy/8395672002?gh_jid=8395672002",1770817399,"Miro is looking for a Machine Learning Research Engineer to serve as the technical "North Star" for our Machine Learning organization. You will operate as an Individual Contributor, driving the architectural decisions behind the "Intelligent Canvas."Your challenge is unique in the industry: You are not just processing text. You are building models that understand spatial relationships, visual diagrams, and unstructured collaboration. You will research, prototype, and ship novel architectures that combine Large Language Models (LLMs), Computer Vision, and Graph Neural Networks (GNNs) to make Miro the smartest collaboration platform on earth.<h4>What you’ll do</h4><ul><li>Design, train, and ship production-grade ML models—including deep learning, NLP, and computer vision systems—that solve complex business problems and power core product features.</li><li>Conduct deep exploratory research on massive datasets to uncover novel patterns in user behavior and content creation, translating raw data insights into new predictive modeling opportunities.</li><li>Apply advanced fine-tuning strategies (e.g., PEFT, LoRA) to adapt state-of-the-art foundation models to specific domain tasks, rigorously experimenting to maximize performance.</li><li>Architect scalable ML pipelines for data processing, feature engineering, training, and evaluation, ensuring high data quality and system reliability.</li><li>Optimize model performance for latency, throughput, and resource utilization, balancing model complexity with production constraints (e.g., overfitting vs. underfitting, compute efficiency).</li><li>Collaborate cross-functionally with data engineers, product managers, and software engineers to translate business requirements into technical ML specifications and integrate models into user-facing applications44.</li><li>Champion MLOps excellence by automating deployment workflows, implementing CI/CD for ML, and establishing robust monitoring for model drift and health.</li><li>Stay at the forefront of ML research, evaluating novel algorithms and techniques (e.g., Transformer architectures, quantization) to drive innovation and technical strategy.</li></ul><h4>What you’ll need</h4><ul><li>Strong foundation in ML theory and statistics, including hypothesis testing, probability distributions, regression, classification, and optimization techniques.</li><li>Solid engineering fundamentals. You are comfortable writing production-level Python and have a deep understanding of data structures, algorithms, and distributed system design.</li><li>Deep proficiency in Python and the modern ML stack, with hands-on experience using libraries like Pandas, NumPy, Scikit-learn, and deep learning frameworks (PyTorch, TensorFlow).</li><li>Gradient Debugging: Expertise in PyTorch or JAX, including experience with distributed training (e.g., DDP, FSDP) and debugging complex gradient issues.</li><li>Applied Research: Ability to read, implement, and improve upon the latest academic papers (NeurIPS, ICML, CVPR). You don't just use libraries; you understand the math underneath them and can reproduce results in peer-reviewed papers.</li><li>Track record of end-to-end ML delivery, from exploratory data analysis (EDA) and feature engineering to training, validation, and deploying models in a production environment.</li><li>Experience with large-scale systems, capable of designing resilient architectures that handle vast datasets and high-throughput inference requests.</li><li>Strong engineering mindset, valuing code quality, testing, modularity, and maintainability just as highly as model accuracy.</li></ul>Education + Experience<ul><li>Option A: Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or related field plus ~3+ years of professional ML engineering experience.</li><li>Option B: No formal degree, ~6+ years of industry experience demonstrating equivalent proficiency in building and shipping ML systems.</li></ul><h4>What's in it for you</h4>LON:<ul><li style="font-weight: 400;">Competitive equity package</li><li style="font-weight: 400;">Health insurance for you and your family</li><li style="font-weight: 400;">Corporate pension plan</li><li style="font-weight: 400;">Lunch, snacks and drinks provided in the office</li><li style="font-weight: 400;">Wellbeing benefit and WFH equipment allowance</li><li style="font-weight: 400;">Annual learning and development allowance to grow your skills and career</li><li style="font-weight: 400;">Opportunity to work for a globally diverse team </li></ul>Multi Location: Amsterdam / Berlin / Yerevan / London:<ul><li style="font-weight: 400;">Competitive equity package</li><li style="font-weight: 400;">Lunch, snacks and drinks provided in the office</li><li style="font-weight: 400;">Wellbeing benefit and WFH equipment allowance</li><li style="font-weight: 400;">Annual learning and development allowance to grow your skills and career</li><li style="font-weight: 400;">Opportunity to work for a globally diverse team</li></ul>Recruiter: #LI-MH1<div class="content-conclusion"><h4>About Miro</h4>\nMiro is a visual workspace for innovation that enables distributed teams of any size to build the next big thing. The platform's infinite canvas enables teams to lead engaging workshops and meetings, design products, brainstorm ideas, and more. Miro, co-headquartered in San Francisco and Amsterdam, serves more than 100M users and 250,000 companies collaborate in the Innovation Workspace. Miro was founded in 2011 and currently has more than 1,600 employees in 13 hubs around the world.\nWe are a team of dreamers. We look for individuals who dream big, work hard, and above all stay humble. Collaboration is at the heart of what we do and through our work together we hope to create a supportive, welcoming, and innovative environment. We strive to play as a team to win the world and create a better version of ourselves every day. If this sounds like something that excites you, we want to hear from you!\nCheck out more about life at Miro: \n<ul class="p-rich_text_list p-rich_text_list__bullet" data-stringify-type="unordered-list" data-indent="0" data-border="0">\n<li data-stringify-indent="0" data-stringify-border="0">Youtube: <a class="c-link" href="https://www.youtube.com/@lifeatmiro" target="_blank" data-stringify-link="https://www.youtube.com/@lifeatmiro" data-sk="tooltip_parent">https://www.youtube.com/@lifeatmiro</a></li>\n<li data-stringify-indent="0" data-stringify-border="0">Blog: <a class="c-link" href="https://miro.com/careers/life-at-miro/all/" target="_blank" data-stringify-link="https://miro.com/careers/life-at-miro/all/" data-sk="tooltip_parent">https://miro.com/careers/life-at-miro/all/</a></li>\n<li data-stringify-indent="0" data-stringify-border="0">Instagram: <a href="https://www.instagram.com/mirohq/">https://www.instagram.com/mirohq/</a></li>\n</ul>\n<hr>\nAt Miro, we strive to create and foster an environment of belonging and collaboration across cultural differences. Miro’s mission — Empower teams to create the next big thing — is how we think about our product, people, and culture. We believe that creating big things requires diverse and inclusive teams. Diversity invites all talent with different demography, identities and styles to step in, and inclusion invites them to step closer together. Every day, we are working to build a more diverse Miro, cultivate a sense of belonging for future and current Mironeers around the world, and foster an environment where everyone can collaborate and embrace differences.\nMiro handles and uses personal data of job applicants in line with its <a href="https://miro.com/legal/recruitment-privacy-policy/" target="_blank">Recruitment Privacy Policy</a> found <a href="https://miro.com/legal/recruitment-privacy-policy/" target="_blank">here</a>. </div>","senior","

Requirements

Strong foundation in ML theory and statistics, including hypothesis testing, probability distributions, regression, classification, and optimization techniques.
Solid engineering fundamentals. You are comfortable writing production-level Python and have a deep understanding of data structures, algorithms, and distributed system design.
Deep proficiency in Python and the modern ML stack, with hands-on experience using libraries like Pandas, NumPy, Scikit-learn, and deep learning frameworks (PyTorch, TensorFlow).
Gradient Debugging: Expertise in PyTorch or JAX, including experience with distributed training (e.g., DDP, FSDP) and debugging complex gradient issues.
Applied Research: Ability to read, implement, and improve upon the latest academic papers (NeurIPS, ICML, CVPR). You understand the math behind libraries and can reproduce results in peer-reviewed papers.
Track record of end-to-end ML delivery, from exploratory data analysis (EDA) and feature engineering to training, validation, and deploying models in a production environment.
Experience with large-scale systems, capable of designing resilient architectures that handle vast datasets and high-throughput inference requests.
Strong engineering mindset, valuing code quality, testing, modularity, and maintainability just as highly as model accuracy.

\n\n

What you'll be doing

Design, train, and ship production-grade ML models—including deep learning, NLP, and computer vision systems—that solve complex business problems and power core product features.
Conduct deep exploratory research on massive datasets to uncover novel patterns in user behavior and content creation, translating raw data insights into new predictive modeling opportunities.
Apply advanced fine-tuning strategies (e.g., PEFT, LoRA) to adapt state-of-the-art foundation models to specific domain tasks, rigorously experimenting to maximize performance.
Architect scalable ML pipelines for data processing, feature engineering, training, and evaluation, ensuring high data quality and system reliability.
Optimize model performance for latency, throughput, and resource utilization, balancing model complexity with production constraints.
Collaborate cross-functionally with data engineers, product managers, and software engineers to integrate models into user-facing applications.
Champion MLOps excellence by automating deployment workflows, implementing CI/CD for ML, and establishing robust monitoring for model drift and health.
Stay at the forefront of ML research, evaluating novel algorithms and techniques to drive innovation and technical strategy.

\n\n

Perks and Benefits

Competitive equity package
Health insurance for you and your family
Corporate pension plan
Lunch, snacks and drinks provided in the office
Wellbeing benefit and WFH equipment allowance
Annual learning and development allowance to grow your skills and career
Opportunity to work for a globally diverse team

",[73],"python","count",2,"actionData","errors"]

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