AI Engineer
Tasks
- Architect agentic workflows for research tasks
- Build retrieval systems for patent documents
- Create evals frameworks for model performance
- Design and implement LLM pipelines
- Develop and deploy machine learning algorithms
- Develop data classification techniques
- Implement production data pipelines
- Monitor data pipeline performance and data quality
- Optimize production inference costs and latency
- Perform unit testing profiling and parameter tuning
Perks/Benefits
- 401k matching
- Health coverage
- Hybrid work environment
- Learning opportunities
- Paid parental leave
- Professional development budget
- Unlimited PTO
Skills/Tech-stack
API Design | AWS | Agentic Workflows | Asynchronous programming | BM25 | Data Classification | Data Modeling | Data Warehousing | Deep learning | Evals Frameworks | Fine Tuning | GCP | Golden datasets | Information Retrieval | LLM Pipelines | Language Models | Large Language Models | Machine Learning | Observability | Pandas | Prompt engineering | Python | Re-ranking | Regression testing | Retrieval-Augmented Generation | SQL | Scikit-learn | Spark | Structured Output | Vector Search
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
Regions
Countries
States
Cities
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