At a Glance
- Tasks: Lead cutting-edge research in AI, focusing on LLM/MLLM and Computer Vision solutions.
- Company: Join Axon, a pioneering tech company at the forefront of AI innovation.
- Benefits: Hybrid work model, competitive salary, and opportunities for mentorship and growth.
- Other info: Fast-paced, mission-driven environment with collaborative team culture.
- Why this job: Make a real impact in AI while mentoring the next generation of scientists.
- Qualifications: PhD and 5+ years in machine learning with strong Python/C++ skills.
The predicted salary is between 63000 - 77000 £ per year.
Axon is seeking a highly skilled Machine Learning Scientist to join our AI team in London.
You will lead research and development of LLM/MLLM and Computer Vision solutions across cloud, devices and sensors, guiding projects from concept to product.
The role requires a Ph D and 5+ years of experience, with strong Python/C++ and frameworks like Tensor Flow or Py Torch.
You will mentor junior scientists and collaborate across teams in a fast-paced, mission-driven environment.
#J-18808-Ljbffr
Senior AI Scientist — LLM/MLLM & CV Lead (Hybrid) employer: University of Georgia- FACS
The Quadram Institute Bioscience is an exceptional employer, offering a dynamic and inclusive work environment where cutting-edge research in Food, Microbiome, and Health thrives. Located in the vibrant Norwich Research Park, employees benefit from state-of-the-art facilities and collaborative opportunities with leading scientists and clinicians, fostering both personal and professional growth. With a commitment to equity and diversity, the institute provides flexible working arrangements and values the contributions of all team members, making it an ideal place for those seeking meaningful and impactful careers.
Contact Details:
University of Georgia- FACS Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Senior AI Scientist — LLM/MLLM & CV Lead (Hybrid)
✨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 University of Georgia- FACS!
✨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 Senior AI Scientist — LLM/MLLM & CV Lead (Hybrid) at University of Georgia- FACS.
✨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 University of Georgia- FACS.
✨Apply Directly through Our Website
When you find a suitable opening like Senior AI Scientist — LLM/MLLM & CV Lead (Hybrid) at University of Georgia- FACS, 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 Senior AI Scientist — LLM/MLLM & CV Lead (Hybrid)
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 University of Georgia- FACS, 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 University of Georgia- FACS. 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 University of Georgia- FACS
✨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 University of Georgia- FACS!
✨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.
