AI Engineer - Wexler
Tasks
- Benchmark models on large datasets
- Build RAG pipelines
- Conduct prompt engineering
- Create evaluation pipelines
- Design production LLM agents
- Develop evaluation frameworks
- Implement NLP preprocessing and embeddings
- Maintain structured model outputs
- Optimize token usage cost and latency
- Write Python back end code for data intensive systems
Perks/Benefits
- Budget for learning and professional growth
- Flexible work schedule
- Hybrid office work in London
- Team retreats
Skills/Tech-stack
Cost Optimization | Data Pipelines | Embeddings | Evaluation | Language Models | Large Language Models | Latency optimization | Model Benchmarking | NLP | Prompt engineering | Python | RAG | Tokenization | Vector Databases
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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