At a Glance
- Tasks: Conduct innovative research in neural network architecture and design novel models for real-time AI.
- Company: Join Cartesia, a cutting-edge AI startup founded by PhDs from Stanford, backed by top investors.
- Benefits: Enjoy free meals, comprehensive health insurance, pension plans, and relocation support.
- Why this job: Be part of a dynamic team creating impactful AI solutions in an inclusive and fast-paced environment.
- Qualifications: Deep expertise in architecture design and strong programming skills in PyTorch or TensorFlow required.
- Other info: This is a full-time role based in London, with opportunities for rapid innovation.
The predicted salary is between 28800 - 48000 ÂŁ per year.
About Cartesia
Our mission is to build the next generation of AI: ubiquitous, interactive intelligence that runs wherever you are. Today, not even the best models can continuously process and reason over a year-long stream of audio, video and text—1B text tokens, 10B audio tokens and 1T video tokens—let alone do this on-device.
We\’re pioneering the model architectures that will make this possible. Our founding team met as PhDs at the Stanford AI Lab, where we invented State Space Models or SSMs, a new primitive for training efficient, large-scale foundation models. Our team combines deep expertise in model innovation and systems engineering paired with a design-minded product engineering team to build and ship cutting edge models and experiences.
We\’re funded by leading investors at Index Ventures and Lightspeed Venture Partners, along with Factory, Conviction, A Star, General Catalyst, SV Angel, Databricks and others. We\’re fortunate to have the support of many amazing advisors, and 90+ angels across many industries, including the world\’s foremost experts in AI.
The Role
We’re opening our first ever office in Europe, and looking to hire incredible talent in London to advance our mission of building real-time multimodal intelligence. In this role, you\’ll:
• Conduct groundbreaking research in neural network architecture design to advance the state-of-the-art (SOTA) in alternative architectures (e.g., state space models, efficient Transformers, hybrid architectures).
• Design novel architectures that improve model quality, inference efficiency, and adaptability across diverse deployment environments, from cloud to on-device.
• Explore and develop capabilities such as statefulness, long-range memory, and innovative conditioning mechanisms for enhancing model expressiveness and generalization.
• Investigate how architectural decisions impact model trade-offs, including scalability, robustness, latency, and energy efficiency.
• Develop new frameworks and tools to evaluate architectural innovations, benchmarking performance across research and production settings.
• Collaborate with cross-functional teams to translate architectural research into scalable and impactful systems for real-world applications.
What We’re Looking For
• Deep expertise in architecture design, with experience in researching or deploying advanced architectures (e.g., state space models, transformers, RNN variants, CNN variants).
• Strong understanding of how architectures interact with system constraints, including deployment in cloud environments or on-device.
• Proficiency in designing architectures that balance quality, efficiency, and adaptability across different use cases and modalities (e.g., vision, audio, text).
• Familiarity with generative modeling paradigms like autoregressive and diffusion models, and designing capabilities such as statefulness and conditioning in deep learning models.
• A proven research track record in top-tier ML/AI venues (e.g., NeurIPS, ICML, ICLR, CVPR) or demonstrable contributions to state-of-the-art architectures.
• Exceptional analytical and problem-solving skills, with a focus on experimentation and iterative refinement.
• Strong programming skills in deep learning frameworks such as PyTorch or TensorFlow, and experience with profiling tools for understanding model performance.
Nice-to-Haves
• Prior research or publications in state space models, efficient Transformers or other alternative architectures.
• Research or practical experience in designing architectures for multi-modal systems.
• Early-stage startup experience or a track record of rapid innovation in R&D environments.
Our culture
We’re an in-person team based out of San Francisco, Bangalore & London. We love being in the office, hanging out together and learning from each other everyday.
We ship fast. All of our work is novel and cutting edge, and execution speed is paramount. We have a high bar, and we don’t sacrifice quality and design along the way.
We support each other. We have an open and inclusive culture that’s focused on giving everyone the resources they need to succeed.
Our perks
Lunch, dinner and snacks at the office.
Fully covered medical, dental, and vision insurance for employees.
Pension Plan.
️ Relocation and immigration support.
Your own personal Yoshi.
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Researcher: Model Architecture, UK employer: Cartesia
Contact Detail:
Cartesia Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Researcher: Model Architecture, UK
✨Tip Number 1
Familiarise yourself with the latest advancements in model architectures, especially state space models and efficient Transformers. This knowledge will not only help you during interviews but also demonstrate your genuine interest in the role.
✨Tip Number 2
Engage with the AI research community by attending relevant conferences or webinars. Networking with professionals in the field can provide insights into current trends and may even lead to referrals.
✨Tip Number 3
Showcase your programming skills by contributing to open-source projects related to deep learning frameworks like PyTorch or TensorFlow. This practical experience can set you apart from other candidates.
✨Tip Number 4
Prepare to discuss your past research and its impact on model architecture design. Be ready to explain how your work aligns with Cartesia's mission of building real-time multimodal intelligence.
We think you need these skills to ace Researcher: Model Architecture, UK
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your deep expertise in architecture design and any relevant experience with advanced architectures. Use specific examples from your research or deployment experiences that align with the job description.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and model architecture. Discuss how your background in neural network architecture design can contribute to Cartesia's mission of building real-time multimodal intelligence.
Showcase Your Research Achievements: If you have publications or contributions to top-tier ML/AI venues, make sure to mention them. Highlight any innovative work you've done in state space models or efficient Transformers, as this will resonate well with the hiring team.
Demonstrate Problem-Solving Skills: Provide examples of how you've tackled complex problems in your previous roles. Discuss your analytical skills and any iterative refinement processes you've employed in your research, as these are key qualities they are looking for.
How to prepare for a job interview at Cartesia
✨Showcase Your Research Experience
Be prepared to discuss your previous research projects in detail, especially those related to neural network architecture design. Highlight any publications or contributions to top-tier ML/AI venues, as this will demonstrate your expertise and commitment to the field.
✨Understand the Company’s Mission
Familiarise yourself with Cartesia's mission to build real-time multimodal intelligence. Be ready to articulate how your skills and experiences align with their goals, particularly in advancing state-of-the-art architectures.
✨Demonstrate Problem-Solving Skills
Prepare to discuss specific challenges you've faced in your research and how you approached solving them. This will showcase your analytical abilities and your focus on experimentation and iterative refinement, which are crucial for the role.
✨Be Ready to Discuss Technical Skills
Make sure you can confidently talk about your programming skills in deep learning frameworks like PyTorch or TensorFlow. Be prepared to discuss how you've used profiling tools to understand model performance, as this is essential for the role.