Data Solution Architect / AI Architect
We are seeking an innovative Data Solution Architect/AI Architect to join our expanding team. In this role, you'll play a vital part in crafting solutions that meet diverse requirements and needs. Collaborating closely with teams of data scientists and machine learning engineers, you'll be at the centre of driving innovation.
Your expertise will be instrumental in enhancing the design of AI systems, spanning classical ML and LLMs, on the AWS platform. You'll contribute to the development of new solutions, including data enrichment pipelines and robust building blocks for training, evaluating, and deploying large language models. Join us on this exciting journey!
Responsibilities
- Create an architecture for utilizing and publishing data within the data mesh
- Develop a strategy to identify the specific machine learning tools, models and training sets to construct
- Collaborate with the AI labs, data, infrastructure and platform teams to implement ML-based services using AWS SageMaker
- Analyze the existing AWS account configuration for data scientists and MLEs, working closely with StSt MLE and DevOps experts
- Assess current AI pipelines and their integration with other services
- Design and build infrastructure to facilitate the experimentation and deployment of AI systems
- Cooperate with the AI Labs team to enhance current ML workflows and software development standards
Requirements
- Hands-on production experience as a Data Architect with a production background in design or development
- Industry knowledge in AWS ML services, including AWS SageMaker
- Qualifications in DevOps, Cloud Operations and ML engineering
- Skills in AWS administration and permission management
- Expertise with building enterprise scale ML and LLM solutions
- High proficiency with Docker, IaC (Terraform) and CI/CD (Atlassian Bamboo)
- Ability to build and use model management tools such as MLflow
- Understanding of MLOps
- B2+ English level, both written and spoken
Nice to have
- Competency in setting up and managing vector databases
- Showcase of deploying LLMs at scale
- Familiarity with Kafka
Technologies
- AWS (Amazon Web Services)
- Artificial intelligence
- ML Architecture
