At a Glance
- Tasks: Drive original research in world modeling and mentor a high-output research group.
- Company: Join Odyssey, an AI lab revolutionising robotics and science with world-class talent.
- Benefits: Competitive salary, flexible work environment, and opportunities for professional growth.
- Other info: Collaborative lab culture that values deep thinking and innovation.
- Why this job: Shape the future of AI and make groundbreaking contributions to generative interactive video.
- Qualifications: Strong background in ML research with a focus on generative modelling and leadership experience.
The predicted salary is between 80000 - 120000 £ per year.
Odyssey is an AI lab pioneering general world models: causal, multimodal systems that learn to predict and interact with the world over long horizons. This foundational technology promises to revolutionise robotics, science, healthcare, education, gaming, defence, and beyond. Odyssey’s founders previously pioneered the most complex application of physical AI: self-driving cars. They’ve now brought together a world-class research team from DeepMind, Tesla, Waymo, Meta, Apple, and Wayve, who have made significant contributions to language models (DeepMind Gemini), video models (DeepMind Veo), world models (Wayve GAIA), and autonomous systems (Tesla FSD). Odyssey has raised significant venture capital from GV, Amazon, AMD, EQT, NVIDIA, Natural Capital, In-Q-Tel, Elad Gil, Jeff Dean, Guillermo Rauch, Garry Tan, Kyle Vogt, and researchers from OpenAI, DeepMind, MSL, Recursive, and Thinking Machines.
As we scale our research ambitions, this role is for a scientist who doesn't just execute on known problems but defines new ones. This TLM role sits at the intersection of deep technical research and scientific leadership: you'll own a long-horizon agenda, mentor a small group, and help shape what this field becomes.
What You'll Do
- Define and drive original research into the foundational open problems of world modeling: temporal coherence, causal reasoning, long-horizon prediction, and user‑intent alignment.
- Move beyond diffusion and transformer paradigms, design novel architectures, learning objectives, and training frameworks that reframe what generative interactive video can do.
- Build and mentor a small, high‑output research group, guiding work from hypothesis through experimental validation to prototype demonstration.
- Translate foundational breakthroughs into stable prototypes in close collaboration with engineering. Not incremental improvements, but genuinely new capabilities.
- Publish at top-tier venues (NeurIPS, ICML, ICLR) and actively engage the broader research community to help Odyssey shape the direction of the field.
Who You Are
- A staff-level or senior ML researcher with a strong publication record in generative modeling, video synthesis, multimodal learning, or adjacent areas.
- Someone who works from first principles: you define the problem before reaching for a method, and you build minimal systems to prove what's possible before scaling.
- Motivated by understanding: you care about why models work, not just that they do.
- Experienced leading or mentoring a small research group, with a track record of taking projects from open question to publication or deployment.
- Comfortable in a focused, autonomous lab environment where deep thinking and tight collaboration are the norm.
- Excited to help establish the scientific foundation of a new medium, one that will define how AI perceives and interacts through pixels over the next decade.
Member of Technical Staff, TLM: Research Scientist employer: Odyssey
At Odyssey, we pride ourselves on being an innovative AI lab that fosters a collaborative and intellectually stimulating work environment. Our culture encourages autonomy and deep thinking, allowing researchers to explore groundbreaking ideas in generative media while contributing to the scientific community. Located in London, we offer unique opportunities for professional growth and the chance to be at the forefront of redefining interactive video technology.
StudySmarter Expert Advice🤫
We think this is how you could land Member of Technical Staff, TLM: Research Scientist
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Odyssey!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Member of Technical Staff, TLM: Research Scientist at Odyssey.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Odyssey.
✨Apply Directly through Our Website
When you find a suitable opening like Member of Technical Staff, TLM: Research Scientist at Odyssey, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Member of Technical Staff, TLM: Research Scientist
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Odyssey, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Odyssey. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Odyssey
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Odyssey!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.