AI Engineer
- AI Solution Development:
- Design, develop, and optimize AI algorithms and models tailored to business needs, ensuring scalability and performance.
- Develop APIs and services to make AI functionalities accessible across the organization.
- Data Preparation & Processing:
- Preprocess and prepare diverse data types (PDFs, Word documents, Excel files, HTML, audio, video, and databases) for machine learning models.
- Ensure data quality, security, and readiness for AI applications.
- LLM Applications:
- Build advanced LLM applications, including Retrieval-Augmented Generation (RAG) workflows, fine-tuning, and embedding models.
- Implement reasoning and agent-based systems, leveraging tools like LangGraph, LangChain.
- Evaluate and optimize performance with techniques like RAGAS and advanced retrieval mechanisms.
- Cloud Deployment & Operations:
- Deploy AI and LLM applications to cloud infrastructure (AWS preferred).
- Manage production-grade solutions with tools like Amazon SageMaker, implementing monitoring, scaling, and visibility tools.
- Performance Monitoring & Troubleshooting:
- Track the performance of deployed AI solutions using monitoring tools and feedback mechanisms.
- Continuously improve solution quality by analyzing outputs and addressing identified issues.
- Research & Innovation:
- Stay updated on emerging AI methodologies, frameworks, and technologies.
- Incorporate cutting-edge developments into existing workflows and create reusable AI frameworks.
- Cross-Functional Collaboration:
- Work with stakeholders such as delivery leads, product managers, and domain experts to translate business needs into actionable AI solutions.
- Collaborate with IT and cloud operations teams to ensure seamless integration and scalability of AI tools.
- Documentation & Best Practices:
- Maintain detailed documentation of AI models, processes, and workflows.
- Establish and promote best practices for AI development, deployment, and maintenance across teams.
- Technical Expertise:
- Proficiency in AI techniques such as RAG, LLM fine-tuning, and embedding models.
- Advanced Python programming skills and experience with frameworks like LangGraph, LangChain.
- Expertise in handling large datasets, including vectorized datasets, and using ETL/ELT tools.
- Cloud & MLOps:
- Hands-on experience deploying and managing AI solutions on AWS.
- Familiarity with containerization technologies like Docker and MLOps practices for efficient model lifecycle management.
- Problem Solving & Collaboration:
- Strong analytical and problem-solving skills for tackling AI development challenges.
- Excellent communication skills to collaborate with cross-functional teams and articulate technical concepts clearly.
- Great community: a welcoming culture with in-person and online social events, our fantastic Walk the World charity day and active diversity and inclusion networks
- Broader impact: take up to four days per year to volunteer, with charity match funding available too
- Career opportunity: the opportunity to develop your career with bespoke training and learning, mentoring platforms and on-demand access to thousands of courses on LinkedIn Learning. When it's time for the next step, we encourage and support internal job moves
- Time out: 25 days annual leave, rising to 27 days after two years, plus a birthday leave day and the chance to work from (almost!) anywhere for up to four weeks a year
- A flexible range of personal benefits to choose from, plus company funded private medical cover
- A ShareMatch scheme that allows you to become an Informa shareholder with free matching shares
- Strong wellbeing support through EAP assistance, mental health first aiders, a healthy living subsidy, access to health apps and more
- Recognition for great work, with global awards and kudos programmes
- As an international company, the chance to collaborate with teams around the world
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