At a Glance
- Tasks: Develop innovative symbolic reasoning models and implement them at scale.
- Company: Join Symbolica, an AI research lab transforming machine learning with category theory.
- Benefits: Enjoy competitive pay, equity options, and a collaborative work environment in London.
- Why this job: Work on groundbreaking AI projects that bridge theory and practical application, making a real impact.
- Qualifications: Bachelor’s or Master’s in Computer Science or Applied Mathematics; strong background in abstract mathematics required.
- Other info: This is an onsite role in our vibrant London office, fostering diversity and inclusion.
The predicted salary is between 43200 - 72000 £ per year.
Symbolica is an AI research lab pioneering the application of category theory to enable logical reasoning in machines. We’re a well-resourced, nimble team of experts on a mission to bridge the gap between theoretical mathematics and cutting-edge technologies, creating symbolic reasoning models that think like humans – precise, logical, and interpretable. Our approach combines rigorous research with fast-paced, results-driven execution. We’re reimagining the very foundations of intelligence while simultaneously developing product-focused machine learning models in a tight feedback loop, where research fuels application. Founded in 2022, we’ve raised over $30M from leading Silicon Valley investors to push the boundaries of applying formal mathematics and logic to machine learning. Our vision is to create AI systems that transform industries, empowering machines to solve humanity’s most complex challenges with precision and insight. Join us to redefine the future of AI by turning groundbreaking ideas into reality.
About the role
As a Machine Learning Research Engineer, you will play a crucial role at the intersection of theoretical research and practical application. You’ll collaborate with world-class researchers to develop innovative symbolic reasoning models inspired by abstract mathematics and implement them at scale. This is an opportunity to work on some of the most challenging problems in machine reasoning while contributing to both foundational research and the engineering of real-world systems.
Your Focus
- Conducting research into symbolic and categorical reasoning models, bridging abstract mathematics with machine learning.
- Translating complex theoretical insights into scalable, efficient coding implementations.
- Developing and optimizing machine learning pipelines for structured reasoning tasks, with a focus on interpretability and performance.
- Building robust experimentation platforms for large-scale training and evaluation of models.
- Collaborating with researchers to explore novel architectures and methodologies in logical reasoning and structured data.
- Benchmarking, debugging, and refining models to ensure reliability in real-world applications.
- Staying at the forefront of advancements in mathematics, machine learning, and AI research to inspire new approaches.
About you
- Bachelor’s or Master’s degree in Computer Science, Applied Mathematics, or a related field (PhD is a plus).
- Strong theoretical background in abstract mathematics, particularly category theory, type theory, or symbolic reasoning.
- Expertise in machine learning model development and optimization, with experience in structured data or reasoning tasks.
- Proficiency in at least one functional programming language (e.g., Haskell, Scala) or extensive experience with Python for deep learning applications.
- Solid software engineering skills, including performance optimization, version control, and CI/CD pipelines.
- Experience deploying machine learning models at scale and in production environments.
- Passion for exploring the intersection of mathematics and AI, and a collaborative mindset for working with researchers and engineers.
We offer competitive compensation, including an attractive equity package, with salary and equity levels aligned to your experience and expertise. This is an onsite role based in our London office (66 City Rd). Symbolica is an equal opportunities employer. We celebrate diversity and are committed to creating an inclusive environment for all employees, regardless of race, gender, age, religion, disability, or sexual orientation.
Contact Detail:
Symbolica Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Research Engineer London, UK
✨Tip Number 1
Familiarise yourself with category theory and symbolic reasoning. Since the role heavily focuses on these areas, having a solid understanding will not only help you in interviews but also demonstrate your genuine interest in the field.
✨Tip Number 2
Engage with the latest research in AI and machine learning, particularly around logical reasoning and structured data. Being able to discuss recent advancements or papers during your conversations can set you apart from other candidates.
✨Tip Number 3
Showcase any projects or experiences where you've implemented machine learning models at scale. Be prepared to discuss the challenges you faced and how you overcame them, as practical experience is highly valued in this role.
✨Tip Number 4
Network with professionals in the AI and mathematics communities. Attend relevant meetups or conferences to connect with researchers and engineers, which could lead to valuable insights and potential referrals for the position.
We think you need these skills to ace ML Research Engineer London, UK
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Machine Learning Research Engineer position. Familiarise yourself with symbolic reasoning models and category theory, as these are central to the role.
Tailor Your CV: Highlight your relevant experience in machine learning, software engineering, and abstract mathematics. Make sure to emphasise any projects or roles where you've worked with structured data or developed machine learning models.
Craft a Compelling Cover Letter: Use your cover letter to express your passion for the intersection of mathematics and AI. Discuss specific experiences that demonstrate your expertise in symbolic reasoning and your collaborative mindset when working with researchers.
Showcase Your Technical Skills: In your application, mention your proficiency in functional programming languages and any experience with Python for deep learning. Include examples of how you've optimised machine learning pipelines or deployed models in production environments.
How to prepare for a job interview at Symbolica
✨Showcase Your Theoretical Knowledge
Make sure to highlight your understanding of abstract mathematics, especially category theory and symbolic reasoning. Be prepared to discuss how these concepts can be applied in practical machine learning scenarios.
✨Demonstrate Coding Proficiency
Since the role requires strong coding skills, particularly in functional programming languages like Haskell or Scala, be ready to showcase your coding abilities. You might be asked to solve a problem on the spot, so practice coding challenges beforehand.
✨Discuss Real-World Applications
Prepare examples of how you've previously deployed machine learning models in production environments. Discuss the challenges you faced and how you overcame them, focusing on performance optimization and reliability.
✨Emphasise Collaboration Skills
This role involves working closely with researchers and engineers, so be sure to convey your collaborative mindset. Share experiences where teamwork led to successful outcomes, and express your enthusiasm for contributing to a diverse team.