NLP / LLM Scientist - Applied AI ML Lead - Machine Learning Centre of Excellence

TN United Kingdom; London; On-site; GBP 60,000 - 80,000

Job description

NLP / LLM Scientist - Applied AI ML Lead - Machine Learning Centre of Excellence

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, speech analytics, time series, reinforcement learning, 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 it to tasks such as NLP, speech recognition and analytics, time-series predictions, or recommendation systems.
• 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 or speech recognition and analytics, personalization/recommendation, and hands-on experience and solid understanding of machine learning and deep learning methods.
• PhD in a quantitative discipline, such as 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, 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 industry and continuous integration models and unit test development.
• Knowledge in search/ranking, Reinforcement Learning, or Meta Learning.
• 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.