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.

What you’ll do

• 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 (e.g., overfitting vs. underfitting, compute efficiency).
• 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.
• 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 (e.g., Transformer architectures, quantization) to drive innovation and technical strategy.

What you’ll need

• 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 don't just use libraries; you understand the math underneath them 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.

Education + Experience

• Option A: Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or related field plus ~3+ years of professional ML engineering experience.
• Option B: No formal degree, ~6+ years of industry experience demonstrating equivalent proficiency in building and shipping ML systems.

What's in it for you

LON:

• 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
  

Multi Location: Amsterdam / Berlin / Yerevan / London:

• Competitive equity package
• 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

Recruiter: #LI-MH1

Miro is the online workspace for innovation, used by 100M+ people to build the next big thing. We are seeking a Research Manager to lead the team defining the brain behind the "Intelligent Canvas."

This is not for building a standard GenAI or Recommendation engine. You will lead a team operating at the intersection of Vision, Language, and Graph Theory, working with a dataset unlike any other in the industry: spatial, unstructured, and deeply human collaboration data. You will bridge the gap between open-ended research (LLMs, Diffusion Models, GNNs) and product impact, empowering teams to dream, design, and build faster.

What You'll Do

• Build and lead a world-class applied research team, hiring and mentoring researchers who excel at the intersection of deep learning theory and production engineering.
• Define the research roadmap to support the "Intelligent Canvas," identifying opportunities to model complex user behaviors—from multi-user collaboration on an infinite canvas, to multi-format AI-powered generation (e.g. slide deck, technical diagram, web app prototypes, etc.), and more.
• Pioneer research on unique spatial datasets. Unlike standard text/image corpuses, you will explore massive multimodal and graph-based datasets, uncovering how teams organize information spatially and collaborate together to solve complex multi-modal problems.
• Drive the "Research-to-Product" velocity. You will create the framework for rapidly testing foundation models (e.g., GPT-4, Llama, Stable Diffusion) and fine-tuning them for specific domain tasks (e.g. prototype generation, diagram generation, mindmap generation).
• Cultivate a culture of scientific rigor. Encourage the team to stay at the cutting edge (NeurIPS, CVPR) while maintaining a relentless focus on shipping features that delight users.
• Partner with Engineering & Product Leadership to translate abstract AI capabilities into intuitive solutions that feel like magic to our users.
• Architect organizational processes for model governance, ensuring rigorous evaluation frameworks, reproducibility, and ethical AI practices.

What We're Looking For

• Proven track record of technical leadership: 2+ years of experience managing high-performing Applied Science or ML Engineering teams in a product-led tech company or top-tier research lab.
• Multimodal & GenAI Depth: You don't just use APIs; you understand the architecture of Transformers, Diffusion models, and Graph Neural Networks (GNNs). You can guide a team through the complexities of fine-tuning and RAG at scale.
• A "Product-First" Researcher: You understand that accuracy metrics (F1, AUC) are proxies, not goals. You prioritize user value and latency constraints in production.
• Curiosity for the "Unsolved": You are excited by the ambiguity of modeling "collaboration." How do you quantify a "good brainstorm"? How do you autocomplete a flowchart?
• Strategic Communication: You can articulate the difference between "hype" and "utility" to executive stakeholders and align research efforts with Miro’s long-term strategy.

Education + Experience

• Option A: PhD in Computer Science, Statistics, Mathematics, or related field + 2+ years of people management experience.
• Option B: Master’s degree or equivalent deep technical experience + 5+ years of industry experience in ML, including 2+ years of people management.

Bonus (Nice-to-Have)

• A portfolio of research contributions, including publications in top-tier conferences (NeurIPS, ICLR, KDD) or impactful technical blog posts.
• Familiarity with the modern MLOps stack and experience guiding teams in building their own research infrastructure.

What's in it for you

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 Global Miro benefits board.

Recruiter: #LI-MH1