Researcher, Models (UK)

Researcher, Models (UK)

Full-Time 60000 - 80000 £ / year (est.) No working from home possible
Cartesia

At a Glance

  • Tasks: Conduct groundbreaking research in neural network architecture and design innovative models.
  • Company: Join a pioneering AI startup with a mission to revolutionise human-like intelligence.
  • Benefits: Competitive salary, equity options, health insurance, and flexible PTO.
  • Other info: Collaborative office culture with excellent growth opportunities and visa sponsorship available.
  • Why this job: Make a real impact in AI by advancing state-of-the-art model architectures.
  • Qualifications: Deep expertise in architecture design and strong programming skills in PyTorch or TensorFlow.

The predicted salary is between 60000 - 80000 £ per year.

About Cartesia

Our mission is to architect AI that learns from and interacts with the world like humans do. 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.

About 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.

Your Impact

  • 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 You Bring

  • 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.

More Details

  • In-office policy: We’re an in-person team based out of offices in San Francisco, London and Bangalore. We love being in the office, hanging out together, and learning from each other every day.
  • Visa sponsorship: We provide visa sponsorship support and assess each circumstance on a case-by-case basis. However, visa sponsorship is dependent on many factors, including the role you are applying for, and the location you are going to be based, and so we can't always guarantee success. Your Recruiter will work with you to understand your visa sponsorship needs from the first call.
  • 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 or design along the way.
  • We support each other. We have an open & inclusive culture that’s focused on giving everyone the resources they need to succeed.

Researcher, Models (UK) employer: Cartesia

At Cartesia, we are committed to fostering a dynamic and collaborative work environment in our new London office, where groundbreaking research meets innovative product engineering. Our culture prioritises inclusivity and support, ensuring that every team member has the resources to thrive while contributing to cutting-edge AI advancements. With competitive compensation, opportunities for professional growth, and a focus on rapid execution without compromising quality, Cartesia is an exceptional employer for those looking to make a meaningful impact in the field of AI.

Cartesia

Contact Details:

Cartesia Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Researcher, Models (UK)

Tip Number 1

Network like a pro! Reach out to people in the AI and research community, especially those connected to Cartesia. Attend meetups, webinars, or conferences where you can chat with potential colleagues and show off your passion for cutting-edge models.

Tip Number 2

Showcase your work! Create a portfolio that highlights your research and projects related to neural network architecture design. Make sure it’s easy to access and visually appealing, so it grabs attention when you share it during interviews or networking events.

Tip Number 3

Prepare for technical interviews by brushing up on your deep learning frameworks like PyTorch or TensorFlow. Practice explaining your past projects and how they relate to the role at Cartesia, focusing on the impact of your architectural decisions.

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team and contributing to our mission of building real-time multimodal intelligence.

We think you need these skills to ace Researcher, Models (UK)

Neural Network Architecture Design
State Space Models
Transformers
RNN Variants
CNN Variants
Cloud Deployment
On-Device Deployment

Some tips for your application 🫡

Show Your Passion:When writing your application, let your enthusiasm for AI and model architecture shine through. We want to see that you’re genuinely excited about the work we do at Cartesia and how you can contribute to our mission.

Tailor Your CV:Make sure your CV highlights relevant experience in architecture design and research. We love seeing specific projects or papers that showcase your skills, especially if they relate to state space models or other advanced architectures.

Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon unless it’s necessary. Make it easy for us to see your qualifications and how they align with the role.

Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it helps us keep everything organised!

How to prepare for a job interview at Cartesia

Know Your Models

Make sure you brush up on the latest advancements in neural network architectures, especially state space models and efficient Transformers. Be ready to discuss your own research and how it aligns with the company's mission of pioneering model architectures.

Showcase Your Problem-Solving Skills

Prepare to share specific examples of how you've tackled complex problems in your previous work. Highlight your analytical skills and your approach to experimentation and iterative refinement, as these are crucial for the role.

Understand Deployment Environments

Familiarise yourself with how different architectures perform in various deployment settings, from cloud to on-device. Being able to discuss the trade-offs between scalability, robustness, and efficiency will impress your interviewers.

Collaborate and Communicate

Since the role involves working with cross-functional teams, be prepared to talk about your experience collaborating with others. Share how you’ve translated architectural research into practical applications, showcasing your ability to communicate complex ideas clearly.