Senior AI Engineer
Tasks
- Build deployment pipelines
- Collaborate with product managers tech leads and software engineers
- Create evaluation harnesses
- Define model evaluation practice
- Develop LLM features in production
- Ensure secure scalable responsible AI use
- Establish MLOps foundations
- Implement monitoring for latency accuracy drift
- Improve reproducibility
- Manage model and prompt versioning
- Mentor AI engineers
- Optimize on prem LLM serving
- Set AI engineering patterns and best practices
Perks/Benefits
- Health insurance
- Hybrid work model
- Lunch scheme
- Pension scheme
- Professional development support
- Remote flexibility
- Six weeks holiday
- Social events
Skills/Tech-stack
AI Agents | Accuracy Monitoring | Data Drift | Data Drift Detection | Deterministic testing | Drift Detection | Evaluation | Fine Tuning | Golden datasets | Human evaluation | LLM | LLM-as-a-Judge | LOCAL model | Latency monitoring | Local Model Serving | MLOps | Machine Learning | Model Deployment | Model Serving | Model versioning | Monitoring | On-prem | On-prem infrastructure | Prompt engineering | Prompt versioning | Python | RAG | Reference Based Metrics | Regression testing | Reproducibility | Retrieval-Augmented Generation
Education
N/A
Roles
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