3 days ago
Responsibilities
- Architect and develop autonomous AI systems using multi-modal large language models.
- Design and implement agentic workflows with prompt engineering and data integrations.
- Fine-tune and deploy large language and multi-modal models for scalability and performance.
- Build scalable MLOps pipelines and cloud-native AI applications.
- Collaborate with clients and teams to shape AI engineering strategy and drive GenAI adoption.
Requirements
- Bachelor’s degree or higher in Computer Science, AI, Engineering, or a related STEM field.
- Proven experience deploying LLMs and multi-modal AI models in enterprise environments.
- Strong software engineering skills in Python, including backend development and API design.
- Solid understanding of scalable MLOps and cloud-native AI deployment architectures.
- Excellent communication and stakeholder management skills in agile environments.
Benefits
- Discretionary bonus, competitive pension, health insurance, and life insurance.
- Access to mental health resources and consultations.
- Family-friendly leave policies and backup care sessions.
- 5 weeks of annual leave with flexible holiday options.
- Minimum 40 hours of training annually and a dedicated business coach.
- Convenient online GP services and additional perks like gym access and travel insurance.