AI Engineer

Job Description

My client - a Global media company - are seeking to recruit an experienced AI Engineer to join their team. You will be responsible for providing technical expertise and leadership across all aspects of AI engineering process, from data acquisition, tagging, embedding, protection and storage. Work closely with data scientists, delivery leads, product managers, content matter experts, and technology teams to develop, automate and scale-up advanced AI solutions to address key customer problems whilst also helping to develop methodologies and reusable solutions.

Duties Include

• Prepare and preprocess data to ensure it is ready for use by machine learning models and AI solutions.
• Work with a variety of data types including PDFs, Word documents, Excel files, HTML, audio, video, and text, as well as various databases.
• Build LLM applications including RAG applications, fine-tuning LLMs and embedding models, agent/reasoning applications.
• Deploy LLM applications to cloud infrastructure (on AWS is plus).
• Manage production-grade LLM application involving RAG evaluation and improvements (RAGAS, advanced retrieval techniques), monitoring and visibility tooling and scaling LLM applications (Amazon SageMaker).
• Stay Current with Emerging Technologies: Keep up-to-date with the latest developments in data engineering, machine learning, and AI technologies to continually enhance data capabilities.

Requirements

• Strong understanding and hands-on experience in various ML techniques and algorithms, including RAG, fine-tuning models and working with large language models.
• Extensive Langchain and Python programming languages, essential for AI development and data manipulation tasks.
• Proficiency in handling and processing large datasets, ensuring data quality and accessibility, including expertise in vectorized datasets.
• Experience with Data Integration Tools: Proficiency in ETL/ELT tools and practices.
• Competency in deploying and managing AI solutions on AWS cloud infrastructure.
• Experience with containerization technologies like Docker.
• Understanding and application of MLOps practices for efficient model life cycle management.
• Knowledge of data security and privacy practices.

Additional Skills

• Effective problem-solving skills to address challenges encountered in AI development projects.
• Strong collaboration and communication skills for effective teamwork and conveying technical concepts clearly to stakeholders.
• Knowledge and experience in MarTech preferred, applied in AI development projects.
• Willingness to continuously learn and adapt to new technologies and methodologies in AI and data engineering.

Company Offer

Excellent Benefits, Training And Career Progression