At a Glance
- Tasks: Lead innovative AI projects using NLP and LLMs to solve real-world challenges.
- Company: Join a cutting-edge 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 significant impact in AI while collaborating with top experts in the field.
- 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.
Applied AI Lead - NLP & LLM Scientist (Real-World ML) in London employer: Aumni
Join a forward-thinking team at the Machine Learning Center of Excellence in London, where innovation meets collaboration. As an Applied AI Lead, you'll have the opportunity to work with cutting-edge technologies in a supportive environment that values continuous learning and professional growth. With a strong commitment to diversity and inclusion, we offer a dynamic workplace that encourages creativity and the pursuit of excellence in solving real-world challenges through machine learning.
StudySmarter Expert Advice🤫
We think this is how you could land Applied AI Lead - NLP & LLM Scientist (Real-World ML) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups or conferences, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to NLP and LLMs. This is your chance to demonstrate your hands-on experience and passion for machine learning.
✨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! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at the Machine Learning Centre of Excellence.
We think you need these skills to ace Applied AI Lead - NLP & LLM Scientist (Real-World ML) in London
Some tips for your application 🫡
Show Your Passion for AI:When writing your application, let your enthusiasm for machine learning and AI shine through. We want to see that you’re not just qualified, but genuinely excited about the field and eager to learn more.
Tailor Your Experience:Make sure to highlight your relevant experience in NLP, LLMs, and deep learning. We’re looking for specific examples of how you’ve applied these skills in real-world scenarios, so don’t hold back!
Collaborative Spirit:Since we thrive in a collaborative environment, emphasise your teamwork skills. Share instances where you’ve worked with cross-functional teams to deploy solutions, as this is key to our success.
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 this exciting opportunity in our Machine Learning Centre of Excellence.
How to prepare for a job interview at Aumni
✨Know Your Stuff
Make sure you brush up on your NLP and LLM knowledge. Be ready to discuss specific projects you've worked on, the tools you used, and the outcomes. This role demands a solid understanding of machine learning methods, so be prepared to dive deep into technical discussions.
✨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 recently. This will show that you're not just qualified but genuinely passionate about the field.
✨Collaboration is Key
Since this role involves working with various teams, highlight your collaborative experiences. Share examples of how you've successfully partnered with business and tech teams in the past. Emphasise your ability to communicate complex concepts clearly to both technical and non-technical audiences.
✨Prepare for Problem-Solving
Expect to tackle real-world problems during the interview. Prepare to discuss how you would approach designing experiments or developing machine learning models for specific tasks. Think about metrics for success and how they align with business goals, as this will showcase your analytical thinking.