AI Engineer I
Tasks
- Build document processing pipelines with OCR
- Build production scale AI agent systems
- Build semantic caching and embedding retrieval
- Create GraphRAG and long context strategies
- Deploy and optimize document understanding pipelines
- Develop evaluation frameworks using LLM as judge
- Develop real time exception handling for shipments
- Develop scalable microservices with observability
- Fine-tune LLMs for domain tasks
- Implement event driven architectures for real time tracking
- Implement quantization and distillation for model optimization
- Implement secure multi tenant systems
- Monitor and evaluate agent performance
- Optimize LLM and SLM deployment strategies
- Optimize model routing and fallback strategies
- Orchestrate LLM workflows
- Prevent prompt injection and validate outputs
Perks/Benefits
- 401k match
- Commuter benefits
- Employee stock option program
- Global recharge days
- Learning and development opportunities
- Life insurance
- Medical, dental, vision benefits
- PTO
- Paid parental leave
- Short-term Disability Insurance
- Technology reimbursement
- Volunteer days
- Wellness stipend
Skills/Tech-stack
AWS Bedrock | AWS SageMaker | Axolotl | BitsAndBytes | DPO | DeepSpeed | Embeddings | Event Driven | Event-driven architecture | FastAPI | Feature Stores | GPU clusters | GraphRAG | Injection prevention | JAX | Kafka | Kubernetes | LLM-as-judge | Langchain | Langgraph | Langsmith | Layout Understanding | LoRA | Long Context | Microservices | Model Distillation | Multi provider redundancy | OCR | Observability | Output Validation | PEFT | PostgreSQL | Prompt injection | Prompt injection prevention | PyTorch | Python | QLoRA | Quantization | RLHF | Redis | Regression testing | Retrieval-Augmented Generation | Semantic Caching | Transformers | Vector Databases | Weights and Biases
Education
N/A
Roles
AI | AI Engineer | Engineer
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