Staff ML Engineer
Tasks
- Build production pipelines and feedback loops
- Build tool using agents and assistants
- Collaborate with data engineering and software engineering
- Conduct technical mentorship and design reviews
- Create observable and tested AI products
- Define success metrics and communicate trade offs
- Define technical direction for AI systems
- Deploy LLM systems with guardrails and safety
- Design build and deploy LLM applications
- Develop RAG pipelines
- Document findings and lead technical discussions
- Implement prompting and evaluation harnesses
- Monitor hallucinations latency and cost
- Productionize models from notebook to production
- Set evaluation and monitoring for quality regressions
Perks/Benefits
- Continuous training
- Fruit in office
- Gym access
- Language classes
- Multicultural environment
- Office breakfast
- Pet friendly
- Private health insurance
- Savings with expense benefits
Skills/Tech-stack
Cost Optimization | Embeddings | Guardrails | LLMOps | Langchain | Latency optimization | MLOps | Machine Learning | Model Evaluation | Model Monitoring | Observability | Orchestration | Prompt engineering | Python | RAG | Retrieval-Augmented Generation | SQL | Safety | Testing | Vector Databases
Education
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