At a Glance
- Tasks: Drive projects from research to real-world applications in neurosymbolic AI.
- Company: Join UnlikelyAI, a leader in innovative AI solutions focused on explainability and reasoning.
- Benefits: Enjoy hybrid work options, competitive salary, and generous share options.
- Why this job: Be part of a collaborative team tackling cutting-edge challenges in AI technology.
- Qualifications: 2+ years in deep learning, Python expertise, and strong communication skills required.
- Other info: Diversity is key; we welcome unique perspectives to solve complex problems.
The predicted salary is between 43200 - 72000 £ per year.
At UnlikelyAI, we are looking for a Senior Applied Scientist to join our Applied Science team. This is a high-impact individual contributor position. You will help drive the end-to-end lifecycle of projects: from identifying opportunities in literature, through proof-of-concept, to real-world production. Your work will sit at the cutting edge of Machine Learning and reasoning systems, with a particular focus on neurosymbolic AI, complex planning, and fully explainable architectures.
Why Join Us?
- Team: You will join a world-class group of smart, collaborative people who are deeply motivated by challenge. We move fast, support each other, and genuinely enjoy the ride.
- Vision: Our mission is to build a novel neurosymbolic AI framework that unlocks new frontiers in explainability and reasoning - and you will be instrumental in shaping that.
- Tech: Our technology is truly novel. You will get the chance to explore original ideas, tackle unsolved problems, and help define new best practices in an environment where creativity and rigour go hand in hand.
What You Will Do:
- Convert cutting-edge research in neurosymbolic AI into real, production-grade language generation systems.
- Design and experiment with hybrid neurosymbolic architectures that challenge current thinking in reasoning and planning.
- Lead applied research projects end-to-end: from ideation and literature review to prototyping and deployment.
- Write high-quality, robust code that integrates neural and symbolic components.
- Collaborate with a team of scientists and engineers, articulating complex ideas clearly to technical and non-technical audiences.
- Analyse and inspect large-scale datasets to support neural training and symbolic extraction.
What We Are Looking For:
- Deep learning expertise with significant industry experience, and c. 2+ years applying it to language generation, including working with Large Language Models, neurosymbolic integration and knowledge representation.
- Experience with Python and common ML Frameworks like Pytorch, HF Transformers, Tensorflow, JAX.
- Track record working as an independent contributor capable of end-to-end development with demonstrable experience in utilising and deploying transformer models.
- Deep knowledge of machine learning fundamentals and cloud experience.
- Enthusiasm to learn and get up to speed with cutting-edge technologies which you may not already be deeply familiar with.
- Excellent verbal and written communication skills with a proven track record of mentoring and coaching others.
- Capable of working collaboratively and proactively in a fast-paced environment with scientists, engineers, and non-technical stakeholders.
Desirable:
- Use of Python libraries that encourage best practices such as pytest, pylint, black etc.
- Experience with symbolic reasoning engines and integration with neural networks.
- Strong technical writing skills as evidenced by relevant publications or blogs.
- Start-up experience.
- Git/Github proficiency working with cloud platforms for deploying hybrid AI systems.
Please see our Company Principles to understand the core things we value - in particular, we are looking for exceptional people who are willing to tackle some of the most difficult technical problems there are, in order to create something extraordinary with huge impact.
Location: We are currently operating a hybrid scheme with a small office near Holborn tube station available to anyone who wants to work there. We also have occasional team days where everyone meets face to face and days where people work heads down from home, communicating with colleagues using Slack and Zoom.
Compensation: Compensation will be through salary and generous share options. The company has a tax-efficient EMI share option scheme set up (not available to larger companies) which allows us to provide real exposure to the success of the company without taxes being due when they are paid.
Equal Opportunities: We are committed to having a truly diverse team where everyone is encouraged to be their authentic selves. We, therefore, do not discriminate in employment based on gender, race, religion, sexual orientation, national origin, political affiliation, disability, age, marital status, medical history, parental status or genetic information. Having a broad mix of people helps us to be the best we can.
Senior Applied Scientist employer: UnlikelyAI
Contact Detail:
UnlikelyAI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Applied Scientist
✨Tip Number 1
Familiarise yourself with the latest research in neurosymbolic AI and language generation. Being able to discuss recent advancements and how they relate to the role will show your genuine interest and expertise during interviews.
✨Tip Number 2
Network with professionals in the field of machine learning and neurosymbolic AI. Attend relevant conferences or webinars, and engage with thought leaders on platforms like LinkedIn to build connections that could help you get noticed.
✨Tip Number 3
Prepare to demonstrate your coding skills in Python and familiarity with ML frameworks. Consider working on a personal project that showcases your ability to integrate neural and symbolic components, as this will provide concrete examples to discuss.
✨Tip Number 4
Brush up on your communication skills, especially in explaining complex concepts to non-technical audiences. Practising how to articulate your ideas clearly can set you apart, as collaboration is key in this role.
We think you need these skills to ace Senior Applied Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your deep learning expertise and relevant industry experience. Focus on your work with language generation, Large Language Models, and any projects involving neurosymbolic integration.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company's mission. Discuss how your skills align with their needs, particularly in areas like hybrid neurosymbolic architectures and technical writing.
Showcase Your Projects: Include specific examples of past projects where you led applied research from ideation to deployment. Highlight your ability to write robust code and collaborate with diverse teams, as this is crucial for the position.
Demonstrate Communication Skills: Since excellent verbal and written communication skills are essential, consider including links to relevant publications or blogs that showcase your ability to articulate complex ideas clearly to both technical and non-technical audiences.
How to prepare for a job interview at UnlikelyAI
✨Showcase Your Deep Learning Expertise
Be prepared to discuss your experience with deep learning, particularly in language generation. Highlight specific projects where you've applied Large Language Models and neurosymbolic integration, as this will demonstrate your fit for the role.
✨Demonstrate Your Coding Skills
Since writing high-quality, robust code is crucial for this position, be ready to share examples of your work with Python and ML frameworks like PyTorch or TensorFlow. Consider discussing any best practices you follow, such as using pytest or pylint.
✨Communicate Complex Ideas Clearly
You’ll need to articulate complex concepts to both technical and non-technical audiences. Practice explaining your past projects in simple terms, focusing on the impact and outcomes rather than just the technical details.
✨Emphasise Collaboration and Proactivity
This role requires working closely with a diverse team. Share examples of how you've successfully collaborated in fast-paced environments, and highlight any mentoring experiences that showcase your ability to support others.