At a Glance
- Tasks: Drive innovative projects in neurosymbolic AI from concept to production.
- Company: Join UnlikelyAI, a cutting-edge tech company with a collaborative spirit.
- Benefits: Competitive salary, share options, hybrid work model, and a supportive team environment.
- Why this job: Be at the forefront of AI technology and make a significant impact.
- Qualifications: Deep learning expertise, Python skills, and a passion for cutting-edge tech.
- Other info: Diverse team culture with excellent growth opportunities and mentorship.
The predicted salary is between 28800 - 48000 Β£ per year.
At UnlikelyAI, we\βre looking for a Senior Applied Scientist to join our Applied Science team. This is a high-impact individual contributor position.
You\βll 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 β You\βll 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 β Our mission is to build a novel neurosymbolic AI framework that unlocks new frontiers in explainability and reasoning β and you\βll be instrumental in shaping that.
Tech β Our technology is truly novel. You\βll 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\βll 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\βre 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 β 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: Unlikely Artificial Intelligence Limited.
Contact Detail:
Unlikely Artificial Intelligence Limited. Recruiting Team
StudySmarter Expert Advice π€«
We think this is how you could land Senior Applied Scientist
β¨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at UnlikelyAI. A friendly chat can open doors that applications alone can't.
β¨Tip Number 2
Show off your skills! Prepare a portfolio or a GitHub repository showcasing your projects, especially those related to neurosymbolic AI and language generation. This will give you an edge during interviews.
β¨Tip Number 3
Practice makes perfect! Get comfortable discussing complex ideas clearly. Mock interviews with friends or mentors can help you articulate your thoughts better, especially for technical roles.
β¨Tip Number 4
Apply through our website! Itβs the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining our team at UnlikelyAI.
We think you need these skills to ace Senior Applied Scientist
Some tips for your application π«‘
Show Your Passion for AI: When you write your application, let your enthusiasm for neurosymbolic AI and machine learning shine through. We want to see that you're not just qualified, but genuinely excited about the work we do and the challenges we tackle.
Tailor Your Experience: Make sure to highlight your relevant experience in language generation and deep learning. Weβre looking for someone who can lead projects end-to-end, so be specific about your past roles and how they relate to what weβre doing at UnlikelyAI.
Communicate Clearly: Your written communication skills are key! We need someone who can articulate complex ideas clearly. Use your application to demonstrate your ability to explain technical concepts in a way thatβs easy to understand for both technical and non-technical audiences.
Apply Through Our Website: Donβt forget to apply through our website! Itβs the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, it shows youβre serious about joining our team!
How to prepare for a job interview at Unlikely Artificial Intelligence Limited.
β¨Know Your Stuff
Make sure you brush up on your deep learning expertise and be ready to discuss your experience with language generation, especially with Large Language Models. Familiarise yourself with neurosymbolic AI concepts and be prepared to explain how you've applied them in real-world scenarios.
β¨Showcase Your Projects
Bring examples of your past projects that demonstrate your ability to lead applied research from ideation to deployment. Be ready to discuss the challenges you faced, how you overcame them, and the impact your work had on the team or project.
β¨Communicate Clearly
Since you'll be collaborating with both technical and non-technical folks, practice articulating complex ideas in a simple way. Prepare to explain your thought process and findings clearly, as this will show your ability to bridge the gap between different audiences.
β¨Embrace the Culture
UnlikelyAI values collaboration and creativity, so be sure to express your enthusiasm for working in a fast-paced environment. Share examples of how you've supported your teammates in the past and how you can contribute to building a positive team culture.