In this role, you will leverage the latest research in Natural Language Processing and statistical machine learning to build AI-powered products that automate processes and enhance decision-making. You will collaborate with software engineering teams to design scalable Machine Learning services and communicate AI capabilities to diverse audiences.
Job Responsibilities:
- Develop and implement machine learning models and algorithms to address complex operational challenges.
- Design and deploy generative AI applications and agents to automate and enhance business processes.
- Collaborate with stakeholders to understand business needs and translate them into technical solutions.
- Analyse large datasets to extract actionable insights and support data-driven decision-making.
- Ensure the scalability and reliability of AI/ML solutions in a production environment.
- Stay informed about the latest advancements in AI/ML technologies and integrate them into our operations.
Required qualifications, capabilities and skills:
- Advanced degree in a STEM field, with relevant experience in AI/ML.
- Experience in deploying AI/ML applications in a production environment, with skills in deploying models on AWS platforms such as SageMaker or Bedrock.
- Familiarity with MLOps practices, covering the full cycle from design, experimentation, deployment, to monitoring and maintenance of machine learning models.
- Expertise in machine learning frameworks such as TensorFlow, PyTorch, PyTorch Lightning, or Scikit-learn.
- Proficiency in Python with a strong emphasis on code quality and reliability through use of comprehensive testing.
- Experience with generative AI models, both as cloud service APIs (e.g. OpenAI) and open source (e.g. Huggingface).
- Experience with integrating user feedback to establish data flywheels and self-improving AI applications.
- Solid understanding of data preprocessing, feature engineering, and model evaluation techniques.
- Familiarity with cloud platforms (AWS).
- Excellent problem-solving skills and the ability to work independently and collaboratively.
- Strong communication skills to effectively convey complex technical concepts to non-technical stakeholders.
Preferred qualifications, capabilities and skills:
- A Ph.D. is a plus but not required
- Experience in the financial services industry, particularly within investment banking operations.
- Experience in developing AI solutions using agentic frameworks.
- Experience fine-tuning LLMs with advanced techniques.
- Experience with prompt optimisation to enhance the performance and effectiveness of prompt engineering.