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- Tasks: Lead the development of machine learning models for large datasets and conduct impactful experiments.
- Company: Join a renowned multinational company based in the UK, known for innovation and excellence.
- Benefits: Enjoy competitive salary, immigration support, and the chance to work with a diverse global team.
- Why this job: This role offers hands-on experience in cutting-edge AI technology and collaboration with top professionals.
- Qualifications: PhD or Master's in CS, CE, ML; programming skills in Java, C++, Python; experience in machine learning.
- Other info: Opportunity to gain international experience and contribute to significant scientific advancements.
The predicted salary is between 43200 - 72000 £ per year.
London, United Kingdom | Posted on 11/25/2024
We\’re thrilled to present an incredible career opportunity! We\’re recruiting on behalf of a renowned multinational company based in the United Kingdom, seeking an Applied Scientist experienced in Generative AI and large models.
What you’ll do:
You will take the lead in developing machine learning models capable of handling very large datasets across various dimensions. With a commitment to scientific precision, you will design and conduct experiments to validate the technical performance and business impact of your approaches. Collaborating closely with fellow scientists and engineering teams, you will ensure your research is seamlessly integrated into production systems.
Key responsibilities:
- Create machine learning algorithms to solve large-scale recommendation challenges.
- Quickly design, test, and refine multiple hypotheses in an uncertain environment, using data analysis and business insights.
- Work closely with software engineers to implement successful experiments into the company’s processes.
- Share findings and insights effectively with both technical and non-technical audiences through presentations and reports.
Requirements
BASIC QUALIFICATIONS
- PhD, or a Master\’s degree and experience in CS, CE, ML or related field research
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience programming in Java, C++, Python or related language
- Experience in building machine learning models for business application
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
PREFERRED QUALIFICATIONS
- Experience in professional software development
Additional Information:
- Immigration support: The company provides support for your immigration process to the United Kingdom.
- Competitive Salary: Enjoy a competitive salary package reflective of your skills and experience.
- Global Experience: Gain international experience by working with a diverse team in a dynamic region.
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Applied Scientist employer: Menaalliances
Contact Detail:
Menaalliances Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied Scientist
✨Tip Number 1
Familiarise yourself with the latest advancements in Generative AI and large models. This will not only help you understand the current landscape but also allow you to engage in meaningful conversations during interviews, showcasing your passion and knowledge in the field.
✨Tip Number 2
Network with professionals in the machine learning community, especially those who have experience in applied science roles. Attend relevant meetups, webinars, or conferences to build connections that could lead to referrals or insider information about the job.
✨Tip Number 3
Prepare to discuss your previous projects in detail, particularly those involving machine learning algorithms and large datasets. Be ready to explain your thought process, the challenges you faced, and how you overcame them, as this demonstrates your problem-solving skills.
✨Tip Number 4
Practice explaining complex technical concepts in simple terms. Since you'll need to share findings with both technical and non-technical audiences, being able to communicate effectively will set you apart from other candidates.
We think you need these skills to ace Applied Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in machine learning, particularly with large datasets and generative AI. Include specific projects or research that demonstrate your expertise in algorithms, data structures, and programming languages like Python or Java.
Craft a Compelling Cover Letter: In your cover letter, express your passion for applied science and how your background aligns with the company's goals. Mention any relevant publications or patents, and explain how your skills can contribute to their projects.
Showcase Your Problem-Solving Skills: Provide examples of how you've designed and tested hypotheses in uncertain environments. Highlight your ability to analyse data and derive business insights, as this is crucial for the role.
Prepare for Technical Questions: Anticipate technical questions related to machine learning models and algorithms during the interview process. Brush up on your knowledge of numerical optimisation and parallel computing, as these are key areas for the position.
How to prepare for a job interview at Menaalliances
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with machine learning models and algorithms in detail. Highlight specific projects where you've successfully implemented these technologies, especially in relation to large datasets.
✨Demonstrate Problem-Solving Skills
Expect to face hypothetical scenarios during the interview. Practice articulating your thought process on how you would approach designing, testing, and refining machine learning hypotheses in uncertain environments.
✨Communicate Effectively
Since you'll need to share findings with both technical and non-technical audiences, practice explaining complex concepts in simple terms. Prepare examples of how you've done this in past roles or projects.
✨Prepare for Collaboration Questions
Collaboration is key in this role. Be ready to discuss your experiences working with software engineers and other scientists. Think of examples that showcase your ability to integrate research into production systems.
