At a Glance
- Tasks: Join us as a Research Engineer to tackle challenging technical problems and create impactful solutions.
- Company: Unlikely AI, a dynamic startup focused on innovative machine learning technologies.
- Benefits: Competitive salary, generous share options, and a hybrid work environment.
- Other info: Collaborative culture with opportunities for growth and exciting projects.
- Why this job: Make a real difference by deploying cutting-edge ML models and optimising performance.
- Qualifications: Experience with deep learning models, strong Python skills, and a passion for learning.
The predicted salary is between 50000 - 70000 £ per year.
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. As a Research Engineer at Unlikely AI, you’ll assist in delivering model prototypes to production. You’ll play a key role in product delivery and designing and implementing new ML features on our platform, which typically includes managing model deployments and ensuring stability. Other projects could include optimising our vector search capabilities. You should have a core understanding of ML fundamentals, and be up to date with the latest LLM models to undertake evaluation of new implementations.
This role includes:
- Implementing, deploying, and monitoring deep learning models, including LLMs.
- Optimising model deployments and designing deep learning model features systems.
- Conducting comprehensive performance evaluations, focusing on latency and accuracy across different implementations.
- Communicating complex solutions to colleagues, facilitating collaboration and knowledge sharing.
- Analysing and inspecting large-scale datasets, effectively managing data scalability and integrity.
Required:
- Experience utilising & deploying deep learning models.
- Strong coding skills in Python, including the use of PyTorch or TensorFlow.
- Enthusiasm to learn and get up to speed with cutting-edge technologies that you may not already be deeply familiar with.
- Strong verbal and written communication skills.
- Experience with cloud infrastructure (e.g. AWS / GCP / Azure).
- Experience with MLOps, with strong expertise in Docker for containerization and orchestration.
- Knowledge of ML model deployment including technologies such as Torchserve, Sagemaker or VertexAI.
- Understanding of modern best practices for agile software development.
- Knowledge of the latest developments in NLP including LLMs and the transformer architecture.
- An understanding of how to keep models stable and performant in production settings.
Desirable:
- Experience with building CI/CD workflows.
- Experience working in a startup.
- Experience with retrieval augmented generation for LLMs and semantic vector search.
- Experience optimising model deployments in terms of latency and throughput.
- Infrastructure-as-code tools, such as Terraform.
Please note this role is not a pure research role and does not involve the creation of academic literature, but you should be very comfortable with reading and utilising academic papers and applying these concepts in your work.
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.
Research Engineer in London employer: Unlikely AI
At Unlikely AI, we pride ourselves on fostering a dynamic and innovative work culture that empowers our Research Engineers to tackle challenging technical problems and contribute to impactful projects. With a hybrid working model based near Holborn, employees enjoy flexibility, collaboration through modern communication tools, and opportunities for professional growth in a supportive startup environment. Our unique EMI share option scheme offers a chance to benefit from the company's success, making us an attractive employer for those seeking meaningful and rewarding careers in machine learning.
StudySmarter Expert Advice🤫
We think this is how you could land Research Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with current employees at Unlikely AI. A personal introduction can make all the difference in getting your foot in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving deep learning models or MLOps. This gives us a tangible way to see what you can bring to the table.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills in Python and familiarising yourself with tools like PyTorch or TensorFlow. We want to see how you tackle real-world problems, so practice coding challenges!
✨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 us you’re genuinely interested in joining our team.
We think you need these skills to ace Research Engineer in London
Some tips for your application 🫡
Know Our Values:Before you start writing your application, take a moment to check out our Company Principles. We’re all about tackling tough problems and creating something extraordinary, so make sure your application reflects that enthusiasm and aligns with what we value.
Show Off Your Skills:When detailing your experience, be specific about your coding skills in Python and any deep learning models you've worked with. Highlight your familiarity with tools like PyTorch or TensorFlow, and don’t forget to mention any cloud infrastructure experience you have – it’s a big plus for us!
Be Versatile:We love candidates who are eager to learn and adapt. In your application, share examples of how you’ve tackled new challenges or learned new technologies in the past. This shows us you’re ready to grow with our evolving Applied Science team.
Apply Through Our Website:We encourage you to submit your application through our website. It’s the best way for us to keep track of your application and ensures you’re considered for the role. Plus, it gives you a chance to showcase your attention to detail right from the start!
How to prepare for a job interview at Unlikely AI
✨Know Your ML Fundamentals
Make sure you brush up on your machine learning fundamentals before the interview. Be prepared to discuss the latest LLM models and how they can be applied in real-world scenarios. This will show that you're not just familiar with the theory but also understand practical applications.
✨Showcase Your Coding Skills
Since strong coding skills in Python are a must, be ready to demonstrate your proficiency. You might be asked to solve a coding problem or explain your previous projects involving PyTorch or TensorFlow. Practising common algorithms and data structures can really help you shine.
✨Communicate Clearly
As a Research Engineer, you'll need to communicate complex solutions effectively. Practice explaining your past projects and technical concepts in simple terms. This will not only help you during the interview but also show your potential for collaboration within the team.
✨Be Versatile and Enthusiastic
The role requires someone who is eager to learn and adapt. Prepare examples of how you've tackled new challenges or learned new technologies in the past. This will demonstrate your enthusiasm for growth and your ability to thrive in a dynamic startup environment.
