At a Glance
- Tasks: Apply advanced machine learning methods to tackle complex challenges in NLP and recommendation systems.
- Company: Join a leading Machine Learning Centre of Excellence in London.
- Benefits: Competitive salary, diverse team, and opportunities for professional growth.
- Other info: Dynamic environment focused on innovation and collaboration.
- Why this job: Make a real impact with cutting-edge AI technologies and collaborate with top experts.
- Qualifications: PhD or MS in a quantitative field with strong machine learning experience.
The predicted salary is between 80000 - 100000 £ per year.
The Machine Learning Center of Excellence invites the successful candidate to apply sophisticated machine learning methods to a wide variety of complex tasks including natural language processing, large language models, and recommendation systems.
The candidate must excel in working in a highly collaborative environment together with the business, technologists and control partners to deploy solutions into production. The candidate must also have a strong passion for machine learning and invest independent time towards learning, researching and experimenting with new innovations in the field. The candidate must have solid expertise in Deep Learning with hands-on implementation experience and possess strong analytical thinking, a deep desire to learn and be highly motivated.
Job Responsibilities
- Research and explore new machine learning methods through independent study, attending industry-leading conferences, experimentation and participating in our knowledge sharing community.
- Develop state-of-the-art machine learning models to solve real-world problems and apply them to tasks such as NLP, LLMs or recommendation systems.
- Produce outputs that lead to high-impact business applications, open-source software, patents, and publications in top AI/ML conferences and journals.
- Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production.
- Drive firm-wide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across different areas of the business.
Required qualifications, capabilities, and skills
- Solid background in NLP and LLMs, and a solid understanding of machine learning and deep learning methods.
- PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science with reasonable industry experience, or an MS with significant industry or research experience in the field.
- Extensive experience with machine learning and deep learning toolkits (e.g. TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas).
- Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals.
- Experience with big data and scalable model training and solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences.
- Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments.
- Curious, hardworking and detail-oriented, and motivated by complex analytical problems.
Preferred qualifications, capabilities, and skills
- Strong background in Mathematics and Statistics and familiarity with the financial services industries and continuous integration models and unit test development.
- Knowledge in search/ranking, Reinforcement Learning or Meta Learning.
- Expertise in recommendation systems.
- Experience with A/B experimentation and data/metric-driven product development, cloud-native deployment in a large-scale distributed environment and ability to develop and debug production-quality code.
- Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journal.
About MLCOE
The Machine Learning Center of Excellence (MCLOE) team partners across the firm to create and share Machine Learning Solutions for our most challenging business problems. In this role you will work and collaborate with a team comprised of a multi-disciplinary community of experts focused exclusively on Machine Learning. On this team you will work with cutting-edge techniques in disciplines such as Deep Learning and Reinforcement Learning.
EEO & Inclusion Statement
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs.
NLP / LLM Scientist - Applied AI ML Lead - Machine Learning Centre of Excellence in London employer: Aumni
Join a forward-thinking team at the Machine Learning Center of Excellence in London, where innovation meets collaboration. As an NLP / LLM Scientist, you'll have the opportunity to work with cutting-edge technologies and contribute to impactful projects while enjoying a supportive work culture that prioritises diversity and inclusion. With ample opportunities for professional growth and access to industry-leading resources, this role is perfect for those passionate about advancing their careers in machine learning.
StudySmarter Expert Advice🤫
We think this is how you could land NLP / LLM Scientist - Applied AI ML Lead - Machine Learning Centre of Excellence in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups or conferences, and connect with potential colleagues on LinkedIn. The more people you know, the better your chances of landing that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to NLP and LLMs. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both techies and non-techies.
✨Tip Number 4
Don't forget to apply through our website! We love seeing passionate candidates who are eager to join our Machine Learning Centre of Excellence. Your next big opportunity could be just a click away!
We think you need these skills to ace NLP / LLM Scientist - Applied AI ML Lead - Machine Learning Centre of Excellence in London
Some tips for your application 🫡
Show Your Passion:Let us see your enthusiasm for machine learning! In your application, share any personal projects or research you've done in NLP or LLMs. This will help us understand your dedication and curiosity in the field.
Tailor Your CV:Make sure your CV highlights relevant experience and skills that match the job description. We want to see your hands-on implementation experience with deep learning toolkits like TensorFlow or PyTorch, so don’t hold back!
Craft a Compelling Cover Letter:Your cover letter is your chance to tell us why you’re the perfect fit for this role. Be sure to mention specific projects or achievements that demonstrate your ability to collaborate and innovate in a team environment.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Aumni
✨Know Your Stuff
Make sure you brush up on your knowledge of NLP and LLMs. Be ready to discuss specific projects you've worked on, the tools you've used like TensorFlow or PyTorch, and how you've applied machine learning methods to solve real-world problems.
✨Show Your Passion
Demonstrate your enthusiasm for machine learning by sharing your independent research or any innovative projects you've undertaken. Talk about conferences you've attended or papers you've read that inspired you, showing that you're committed to continuous learning.
✨Collaboration is Key
Since this role involves working with various teams, be prepared to discuss your experience in collaborative environments. Share examples of how you've successfully partnered with business and technical teams to deploy solutions, highlighting your communication skills.
✨Think Like a Scientist
Be ready to talk about your approach to designing experiments and evaluating model performance. Discuss how you align your work with business goals and share any experiences with A/B testing or data-driven product development to showcase your analytical thinking.