Lead AI Engineer - Pioneering Decision Support SaaS for Healthcare

We are on the lookout for an experienced Lead AI Engineer to join our clients innovative team and play a key role in shaping a revolutionary decision-support SaaS Healthcare platform. This position offers the chance to drive impactful AI solutions in the healthcare domain, leading projects from inception to deployment.

What We're Looking For

Educational Background: Master's degree in a relevant field such as Computer Science, Electrical Engineering, Physics, or Aerospace Engineering. A Ph.D. is highly regarded.
Professional Experience: At least 4 years of hands-on experience in applied Machine Learning roles.
Expertise in Generative AI: Strong knowledge of Generative AI and Large Language Models (LLMs), including deploying LLMs in real-world applications.
Technical Proficiency: Skilled in Python or similar programming languages for AI/ML development, with experience in open-source tools like LangChain.
Data Integration: Familiarity with leveraging multiple data sources to inform AI solutions.
Innovation and Pro-activity: Excited about starting projects from the ground up and employing experimental methods to evaluate solutions through prototypes.
End-to-End Implementation: Capable of building fully operational prototypes, from architecture and data engineering to algorithm development and deployment.
Lifelong Learner: Committed to keeping up with the latest AI advancements.
Adaptability: Comfortable working in a fast-paced, dynamic environment with shifting project priorities.
Methodologies: Experience or knowledge of Agile development practices.
Work Ethic: Results-driven with the ability to meet tight deadlines.
Language Skills: Excellent command of English.Your Role and Responsibilities

Lead AI Initiatives: Spearhead the application of advanced AI technologies to enhance our platform's capabilities.
AI Pipeline Development: Build and implement scalable AI pipelines, ensuring efficient data pre-processing, design engineering, deployment, and monitoring.
LLM Ops Architecture: Design and manage end-to-end LLM Ops solutions using cloud platforms, automation tools, and orchestration frameworks to ensure robust and reproducible AI systems.
Generative AI Innovation: Develop advanced Generative AI solutions, including prompt engineering frameworks for generating insightful and diverse outputs.
Cross-Team Collaboration: Work with multiple teams to identify opportunities for AI-driven innovation and improvement.
Product Enhancement: Collaborate with Engineering and Product teams to translate business needs into technical solutions, optimising our data infrastructure and product performance.
Algorithm Optimisation: Fine-tune AI models and algorithms to handle structured and unstructured data effectively.
Trend Monitoring: Stay ahead of the curve by keeping up with emerging AI trends, applying the latest best practices to projects.
Quality Assurance: Ensure high standards for AI solutions through thorough testing and validation.If you're passionate about leveraging AI to transform healthcare and thrive in a dynamic, forward-thinking environment, we'd love to hear from you