Member of Technical Staff - Applied ML
Tasks
- Build LLM based AI agent applications
- Build experimentation infrastructure
- Build feedback loop systems for continuous improvement
- Build offline and online evaluation frameworks
- Collaborate with engineering and product teams
- Create retrieval and indexing pipelines
- Define golden datasets and metrics
- Deploy and instrument ML systems in production
- Design multi-agent architectures
- Design prompt stacks and instruction hierarchies
- Develop evaluation and benchmarking systems
- Implement guardrails and validation layers
- Implement model orchestration and routing
- Instrument AI systems for regressions
- Monitor latency cost accuracy and reliability
- Parse unstructured documents into structured data
- Run structured ML experiments
Perks/Benefits
Skills/Tech-stack
Agentic Systems | Benchmarking | Data labeling | Deep learning | Distributed Systems | Evaluation | Experiment tracking | Experimentation | Feature Engineering | Guardrails | Information Retrieval | LLM orchestration | Language Models | Large Language Models | Machine Learning | Model routing | Offline evaluation | Online evaluation | PostgreSQL | Prompt engineering | Python | Transformers | Vector indexing
Education
Regions
Countries
States
Cities
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