Applied Research Scientist

Wolt

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 reviews, and raising the bar on ML practices. OUR HUMBLE EXPECTATIONS*  * You have 4+ years of hands-on experience in applied ML with a track record of shipping models to production (a PhD in ML with applied research experience is equally welcome). * You have solid experience in Search: query understanding, query intent prediction, or semantic search. * You are proficient in Python and experienced with ML frameworks and large-scale data processing. * You communicate complex technical ideas clearly and collaborate effectively with cross-functional teams. * Experience with NLP, dense retrieval, learning-to-rank, or embedding-based methods is a strong plus. WHAT WE OFFER In this role, you will have a direct and measurable impact on millions of customers every day. You’ll join a team of world-class applied scientists and engineers in DoorDash, Deliveroo and  Wolt who care about both rigour and craft, tackling problems that are genuinely hard and impactful in ways that few companies can offer. Together with your lead, you will have the opportunity to create a personalised development plan to grow your strengths and to develop new capabilities. 📍 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. We also offer relocation support to help you join us. NEXT STEPS* Once you apply, you will go through 4 steps in our hiring pipeline: * TA Screen: a 30-minute introductory call with one of our Talent Partners to learn about your background and tell you more about the role. * Hiring Manager interview: a conversation covering your domain experience in Search or Personalisation, past projects, AI fluency, and ways of working. We will tell you more about the team, use cases, our tech stack, etc. and it will be your opportunity to ask questions. * Coding & System Design: a technical session focused on ML system design and problem-solving with some of the team’s ML Engineers. * Project / Expertise Deep Dive: an interview with the team’s Applied Scientists, going deep on your domain expertise and past projects. OUR COMMITMENT TO DIVERSITY AND INCLUSION We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. That’s why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel.

Mirelo

Mirelo AI is building the next generation of creative tools by generating realistic sound, speech and music from video. We develop cutting-edge foundational generative AI models that "unmute" silent video content and create custom, hyper-realistic audio for gaming, video platforms, and creators. Our technology empowers global storytellers to transform their content. We recently closed a $41 million Seed round co-led by Andreessen Horowitz and Index Ventures with participation from Atlantic, and are rapidly expanding across Product, Engineering, Go-to-Market, and Growth. About the Role At Mirelo, you’ll work at the centre of how we build the next generation of multimodal video-to-audio models. This role is deeply hands-on and research-heavy: with a great H100/200-per-engineer ratio you explore and build new multimodal models and push the boundaries of what’s possible in music, sound, and speech generation. You’ll collaborate closely across research and engineering, run focused ablations, and translate experimental results into clear next steps for the team. From data curation to deployment, you’ll help shape the full lifecycle of the models that power our products and partnerships. KEY RESPONSIBILITIES * Design, implement and train large-scale multimodal generative models for audio generation (diffusion and/or autoregressive models). * Explore new modeling ideas for audio generation (music, sound, speech) while taking inspiration from the language and image domains. * Develop and experiment with post-training for new capabilities (fine-grained control, in/out-painting, editing, …) * Conduct rigorous ablation studies, get actionable insights and communicate results to the team to discuss new research directions. * Contribute hands-on to all stages of model development including data curation, experimentation, evaluation, and deployment. IDEAL CANDIDATE PROFILE * Hands-on experience in training large-scale generative models in a fast-paced research environment. * Deep understanding of cutting-edge methods and ML research in at least one of the domains: image, language, video or audio (specific audio experience not necessary, but nice to have). * Strong proficiency in PyTorch, transformer architectures, and the full ecosystem of modern deep learning. * Solid understanding of distributed training techniques—FSDP, low precision training, model parallelism * Strong track-record in working on generative models (publications in top-tier venues, open-source contributions or applied ML projects). NICE TO HAVE * Proficiency with profiling, debugging, and optimizing single and multi-GPU operations using tools like Nsight or stack trace viewers. * Strong software engineering skills/experience in collaborating on large codebases that go beyond PhD research code. * Experience with generative models for audio (sound, music or speech) and audio codec design. WHY JOIN? * Join at a pivotal moment. We've secured fresh funding and are gaining traction - now is when your contributions can make a real difference to our success. * True ownership from day one. You'll have genuine autonomy and responsibility. Your ideas and work will directly shape our product and company direction. * Competitive compensation and equity. We offer strong packages that ensure you share in the success you help create. * Build for the next generation of creators. Be part of the innovation that will transform how creators work and thrive. We welcome applications from all individuals, regardless of ethnic origin, gender, disability, religion or belief, age, or sexual orientation and identity.

Prior Labs

WHO WE ARE Foundation models transformed text and images. Structured data - the largest and most consequential data format in the world - stayed untouched. Tables run every clinical trial, every financial model, every scientific experiment, every business decision, and no one had built a foundation model that truly understood them. Until now. What LLMs did for language, we're doing for tables. The next modality shift in AI is happening, and we're hiring the team that makes it. Momentum. We pioneered tabular foundation models and are now the world-leading organization in structured-data ML. Our TabPFN v2 model was published as a Nature cover story and set a new state of the art for tabular machine learning. Since release we've scaled model capabilities 20x+, passed 3.5M+ downloads and 7,500+ GitHub stars, and are seeing accelerating adoption across research and industry - from detecting lung disease with Oxford Cancer Analytics to preventing train failures with Hitachi to improving clinical-trial decisions with BostonGene. The hardest work is ahead. We're scaling tabular foundation models to millions of rows, thousands of features, real-time inference, and entirely new data modalities, while building the infrastructure to run them in production across some of the most demanding industries on earth. These are open problems no one else is working on at this level. Our team. We're a small, highly selective team of 30+ engineers, researchers, and GTM specialists, with backgrounds spanning Google, Apple, Amazon, DeepMind, Meta, Microsoft Research, G-Research, Jane Street, Goldman Sachs, and CERN. We're led by Frank Hutter, Noah Hollmann, and Sauraj Gambhir, and advised by world-leading AI researchers including Bernhard Schölkopf and Turing Award winner Yann LeCun. We ship fast, do top-tier research, and hold each other to an extremely high bar. What's next. In 2025 we raised €9m pre-seed led by Balderton Capital, backed by leaders from Hugging Face, DeepMind, and Black Forest Labs. The next phase of growth is here, which makes this an ideal time to join. CORE AREAS OF IMPACT You'll be among the first scientists collaborating and working an entirely new class of AI models, not just incremental improvements. As an early-stage startup working on foundation models for tabular data, we have countless exciting research ideas and problems to explore - you're sure to find challenges that match your interests and expertise. We are working on problems such as: * Scaling our transformer architectures from 10K to 1M+ samples while maintaining performance * Building multimodal models that combine text and tabular understanding on proprietary data * Developing specialized architectures for time series, forecasting, and anomaly detection * Creating efficient inference methods for production deployment * Researching causal understanding in foundation models * Designing novel approaches for handling multiple related tables WHAT WE'RE LOOKING FOR * Currently pursuing or holding a PhD in Computer Science, Applied Mathematics, Statistics, Electrical Engineering, or a related field (we will also consider exceptional Master's students) * Deep experience with ML frameworks, especially PyTorch and scikit-learn * Strong engineering fundamentals with excellent Python expertise * Experience in data-science and working with tabular data or time series * Publications at top-tier venues (NeurIPS, ICML, ICLR) or significant open-source contributions BENEFITS * Strong mentorship and professional development opportunities * Work with state-of-the-art ML architecture, substantial compute resources, and a world-class team * Comprehensive benefits including healthcare, transportation, and fitness Life at Prior Labs We're a small, ambitious team solving one of the hardest problems in AI, and we're just getting started. You'll work closely with world-class researchers and builders who care deeply about the quality of their craft, the impact of their work, and the people they work with. We move fast, we think rigorously, and we take the time to do things right. If you're excited by hard problems, motivated by real-world impact, and want to be part of building something that matters, we'd love to hear from you. We're building our teams in Berlin, Freiburg, and New York and we believe that when you're working on something as hard and exciting as TabPFN, being in the same room matters. Most of our roles are based in one of our offices but great people come from everywhere, and in exceptional cases we're open to remote. This usually involves frequent travel to one of our offices and the whole company comes together regularly for offsites to think, build, and celebrate together. Our Commitments We believe the best products and teams come from a wide range of perspectives, experiences, and backgrounds. That's why we welcome applications from people of all identities and walks of life, especially anyone who's ever felt discouraged by "not checking every box." We're committed to creating a safe, inclusive environment and providing equal opportunities regardless of gender, sexual orientation, origin, disability, or any other trait that makes you who you are. We care about how your data is handled. Read our Recruiting Privacy Notice to see exactly what we collect, why, and how long we keep it.