Machine Learning Engineer (Multimodal)

Harnham
London
1 year ago
Applications closed

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Machine Learning Engineer (Multimodal) Up to £100,000 London Hybrid/Remote Driving innovation with AI and machine learning to revolutionize financial services and enhance customer experiences. COMPANY Harnham has partnered with a leading Fintech company using advanced AI technology to transform financial services. Their cutting-edge approach has led to the development of innovative financial solutions, making significant strides in areas such as fraud detection, personalized financial advice, and risk management. ROLE: Lead the development of AI algorithms, focusing on AI/ML techniques and Large Language Models (LLMs) to drive innovation in financial services. Build and test machine learning models, advocate for best coding practices, and ensure high-quality results through thorough testing. Collaborate closely with data scientists, financial analysts, and engineers to develop and implement AI/ML tools for data analysis. Leverage expertise in multimodal LLMs, especially in search and retrieval-augmented generation (RAG) technologies, to enhance model performance and application in financial contexts. YOUR SKILLS AND EXPERIENCE: MSc or PhD in a STEM subject. Proven experience with the implementation of Machine Learning models and Large Language Models, including multimodal LLMs. MLOps/DevOps experience with CI/CD pipelines. Proficiency in TensorFlow, Kubernetes, MLFlow, Kafka, and Airflow. Strong Python skills are essential; experience with AWS and Spark is beneficial. Excellent communication skills and experience engaging with team members and stakeholders. Expertise in large-scale computation and experience in a research or tech-driven environment. Familiarity with LLMs and tools like Langchain, with specific exposure to search and retrieval-augmented generation (RAG) technologies. Keen interest in financial technology and the Fintech space. BENEFITS: Salary up to £100,000 Bonus Healthcare & Pension HOW TO APPLY: Please register your interest by sending your CV to Luc Simpson-Kent via the link on this page.

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