At a Glance
- Tasks: Lead a team to innovate the 'Intelligent Canvas' using cutting-edge AI technologies.
- Company: Join Miro, a leading online workspace for over 100 million users.
- Benefits: Competitive salary, flexible work environment, and opportunities for professional growth.
- Other info: Be part of a dynamic team driving impactful AI solutions.
- Why this job: Shape the future of collaboration with groundbreaking research and technology.
- Qualifications: PhD or Master's in relevant fields with strong leadership experience in ML.
The predicted salary is between 80000 - 100000 € per year.
Requirements
- Proven track record of technical leadership: 2+ years managing high‑performing Applied Science or ML Engineering teams in a product‑led tech company or top‑tier research lab.
- Multimodal & GenAI Depth: Understanding of transformers, diffusion models, and graph neural networks; able to guide fine‑tuning and RAG at scale.
- Product‑first researcher: Prioritise user value and latency over pure accuracy metrics.
- Curiosity for the unsolved: Excitement for modelling collaborative behaviours and quantifying “good brainstorming.”
- Strategic communication: Articulate the difference between hype and utility to executive stakeholders and align research with product strategy.
- Option A: PhD in Computer Science/Statistics/Mathematics + 2+ years people‑management experience.
- Option B: Master’s or equivalent deep technical experience + 5+ years industry experience in ML, including 2+ years people‑management.
- (Desirable) Publications in top‑tier conferences (NeurIPS, ICLR, KDD) or impactful technical blogs.
- (Desirable) Familiarity with modern MLOps stack and experience building research infrastructure.
What the job involves
- Miro is the online workspace for innovation, used by 100M+ people. The Research Manager leads the team defining the brain behind the “Intelligent Canvas.”
- Not a standard GenAI or recommendation engine. Lead a team at the intersection of vision, language, and graph theory, working with spatial, unstructured, and deeply human collaboration data.
- Bridge open‑ended research (LLMs, diffusion models, GNNs) and product impact, empowering teams to dream, design, and build faster.
- Build and lead a world‑class applied research team, hiring and mentoring researchers who excel at deep learning theory and production engineering.
- Define the research roadmap for the “Intelligent Canvas,” identifying opportunities to model complex user behaviours—including multi‑user collaboration on an infinite canvas and multi‑format AI‑powered generation (slide deck, technical diagram, web app prototypes).
- Lead research on unique spatial datasets, exploring multimodal and graph‑based data to uncover how teams organise information and collaborate to solve complex multi‑modal problems.
- Drive the research‑to‑product velocity, creating a framework for rapidly testing foundation models (GPT‑4, Llama, Stable Diffusion) and fine‑tuning them for domain tasks (prototype, diagram, mindmap generation).
- Cultivate a culture of scientific rigor, staying current with NeurIPS, CVPR while focusing on shipping features that delight users.
- Partner with Engineering and Product Leadership to translate AI capabilities into intuitive solutions that feel like magic.
- Architect organizational processes for model governance, ensuring rigorous evaluation, reproducibility, and ethical AI practices.
Machine Learning Research Manager in London employer: Deepstreamtech
Miro is an exceptional employer, offering a dynamic work environment where innovation thrives. As a Machine Learning Research Manager, you will lead a talented team at the forefront of AI research, with ample opportunities for professional growth and collaboration on groundbreaking projects. Our culture prioritises scientific rigor and user-centric design, ensuring that your contributions directly impact millions of users worldwide while fostering a supportive atmosphere for continuous learning.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Research Manager in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage in online forums. The more people you know, the better your chances of landing that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to machine learning and applied research. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios specific to machine learning leadership. Think about how you would communicate complex ideas to non-technical stakeholders—this is key!
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Machine Learning Research Manager in London
Some tips for your application 🫡
Show Your Leadership Skills:Make sure to highlight your experience in managing high-performing teams. We want to see how you've led projects and inspired your team to achieve great results, especially in a tech environment.
Demonstrate Your Technical Know-How:Dive into your understanding of multimodal AI and GenAI. Share specific examples of how you've worked with transformers, diffusion models, or graph neural networks, and how you’ve applied this knowledge in real-world scenarios.
Focus on User Value:We’re all about prioritising user experience over just accuracy. In your application, explain how you've balanced technical excellence with delivering real value to users in your past projects.
Be Curious and Innovative:Show us your excitement for tackling unsolved problems! Share any unique approaches you've taken in research or product development that demonstrate your curiosity and innovative thinking.
How to prepare for a job interview at Deepstreamtech
✨Showcase Your Leadership Experience
Make sure to highlight your experience managing high-performing teams. Share specific examples of how you've led projects or initiatives in the past, especially in a product-led tech environment. This will demonstrate your ability to guide and inspire a team effectively.
✨Demonstrate Technical Depth
Be prepared to discuss your understanding of key concepts like transformers, diffusion models, and graph neural networks. Bring examples of how you've applied these technologies in real-world scenarios, particularly focusing on user value and latency over pure accuracy metrics.
✨Communicate Strategically
Practice articulating complex ideas in a way that resonates with executive stakeholders. Be ready to explain the difference between hype and utility, and how your research aligns with product strategy. This will show that you can bridge the gap between technical research and business impact.
✨Cultivate Curiosity and Innovation
Express your excitement for tackling unsolved problems, such as modelling collaborative behaviours. Share any relevant experiences or projects where you've explored innovative solutions, especially in multi-user collaboration contexts. This will highlight your passion for pushing boundaries in research.
