(Senior) Machine Learning Engineer
3 weeks ago
Gravitas has partnered with a well funded FinTech Start-Up specialising in building Gen AI financial advisory solutions for enterprise businesses.
As the Senior Machine Learning Engineer specialising in Generative AI , you will be at the helm of cutting-edge AI projects that will fundamentally reshape how financial decisions are made. Your work will directly influence how personalised, real-time financial insights are delivered, enabling smarter, more efficient advisory services and improving the overall customer experience. This is a unique opportunity to lead transformative AI solutions in a fast-growing sector.
Position: Senior Machine Learning Engineer
Negotiable depending on experience
Benefits: Equity + Benefits package
Sherborne / Remote (occasional travel to London to be on client site)
Lead the development of innovative Generative AI models tailored to the wealth management industry.
Drive the optimisation of large language models (LLMs) to extract deeper insights and enhance prediction capabilities for financial applications.
Spearhead the implementation of Retrieval-Augmented Generation (RAG) systems, improving the AI’s performance in specific financial scenarios.
Lead initiatives for model fine-tuning , ensuring generative models perform optimally in real-world financial contexts.
Design and build scalable AI pipelines capable of managing and processing complex financial data.
Innovate in the field of Conversational AI , enhancing client-advisor interactions with intelligent, real-time decision-making systems.
Develop and deploy AI-driven systems capable of real-time financial data analysis and actionable insights.
Write clean, maintainable, and efficient code, establishing best practices for AI infrastructure within the company.
Collaborate closely with cross-functional teams to integrate AI solutions into the core platform.
6+ years of experience as a Machine Learning Engineer , with a strong track record of impactful AI projects.
~ Expertise in Generative AI , with at least 1 year of hands-on experience working with generative models.
~ Strong experience with Retrieval-Augmented Generation (RAG) and other cutting-edge AI techniques.
~ Proven success in fine-tuning models for specialized applications, particularly in financial services or data-driven domains.
~ Advanced proficiency in Python and deep learning frameworks like PyTorch or TensorFlow .
~ Strong experience with MLOps , ML pipelines , and deployment on cloud platforms like AWS , GCP , or Azure .
~ Solid foundation in software engineering principles, ensuring that code is efficient, scalable, and maintainable.
Experience across a range of Generative AI models and architectures, with an understanding of their practical applications.
Contributions to the AI community , such as research papers, open-source projects, or speaking engagements.
Knowledge of containerisation technologies like Docker and Kubernetes for seamless deployment.
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