
AI Solution Designer
19 hours ago
We are seeking a highly skilled AI Solution Designer to craft innovative artificial intelligence solutions that drive business value. This role involves collaborating with cross-functional teams to develop end-to-end solutions incorporating data ingestion, model training, deployment, and monitoring.
Main Responsibilities:- Cross Disciplinary Solution Design: Engage with stakeholders to understand product requirements and architect end-to-end solutions combining traditional software components with AI/ML models and modern data engineering practices.
- Hands-On Development: Write and maintain production-quality code across backend services, data pipelines, and model inference layers, primarily using Python and at least one other language.
- Data Engineering & Pipeline Construction: Develop and manage data pipelines for ingestion, transformation, and storage, ensuring data quality, schema management, and robust ETL processes that support model training and inference.
- Advanced AI/ML & LLM Expertise: Train, finetune, and deploy machine learning and deep learning models, including large language models (LLMs) and transformer architectures.
- System Optimisation & Scalability: Optimise model performance for production workloads using techniques such as model quantisation, batching, and caching. Scale services using containerisation and orchestration on cloud platforms.
- Collaboration & Mentorship: Collaborate with software engineers, data scientists, and DevOps teams to deliver cohesive solutions. Mentor junior engineers and share best practices in software development, data engineering, and AI/ML.
- Monitoring & Maintenance: Implement observability for data pipelines and AI services. Continuously monitor and iterate models and pipelines based on feedback and new data.
- Bachelor's or Master's degree in Computer Science, Data Engineering, Artificial Intelligence, or related field.
- 5+ years of experience; 6-8 years in software development and data engineering, with at least 3 years of hands-on AI/ML experience.
- Proficiency in Python and deep familiarity with AI/ML frameworks and LLM libraries.
- Hands-on experience building and deploying large language models, embeddings, RAG pipelines, and vector-database-powered applications.
- Strong knowledge of data engineering tools, relational and NoSQL databases, and proficiency in SQL.
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