At a Glance
- Tasks: Lead innovative AI projects using NLP and LLMs to solve real-world challenges.
- Company: Join a forward-thinking 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 diversity.
- 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) employer: Job Search Place Limited
As a leader in the Machine Learning Centre of Excellence, we offer an exceptional work environment in London that fosters collaboration and innovation. Our commitment to employee growth is evident through opportunities for independent research, participation in industry conferences, and engagement with a diverse team of experts. With a strong focus on diversity and inclusion, we ensure that every voice is valued, making us an outstanding employer for those passionate about advancing their careers in machine learning.
StudySmarter Expert Advice🤫
We think this is how you could land Applied AI Lead - NLP & LLM Scientist (Real-World ML)
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the AI and ML community. Attend meetups, conferences, or even online webinars. You never know who might have the inside scoop on job openings or can refer you directly to hiring managers.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to NLP and LLMs. Share your work on platforms like GitHub or even write blog posts about your findings. This not only demonstrates your expertise but also your passion for the field.
✨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 technical and non-technical teams. Mock interviews can be a great way to build confidence!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Tailor your application to highlight your relevant experience in machine learning and deep learning, and let us know how you can contribute to our collaborative environment.
We think you need these skills to ace Applied AI Lead - NLP & LLM Scientist (Real-World ML)
Some tips for your application 🫡
Show Your Passion for AI:When writing your application, let us see your enthusiasm for machine learning and AI. Share any personal projects or research you've done in NLP or LLMs to demonstrate your commitment to the field.
Tailor Your Experience:Make sure to highlight your relevant experience with machine learning and deep learning toolkits like TensorFlow or PyTorch. We want to see how your skills align with the responsibilities of the role, so be specific!
Collaborative Spirit:Since we value collaboration, mention any past experiences where you worked with cross-functional teams. This could be anything from tech partners to business stakeholders—show us how you thrive in a team environment!
Keep It Clear and Concise:Your written application should be easy to read and understand. Avoid jargon where possible and focus on clearly communicating your technical skills and achievements. Remember, we want to get to know you through your words!
How to prepare for a job interview at Job Search Place Limited
✨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've used like TensorFlow or PyTorch, and how you've applied machine learning methods to real-world problems.
✨Show Your Passion
Demonstrate your enthusiasm for machine learning! Talk about any independent research or experiments you've conducted, and mention any conferences you've attended. This shows you're proactive and genuinely interested in the field.
✨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 tech teams to deploy solutions.
✨Communicate Clearly
Practice explaining complex technical concepts in simple terms. You’ll need to communicate effectively with both technical and non-technical audiences, so think of ways to make your explanations relatable and clear.