AI/ML Engineer
Tasks
- Build RAG backed investigation workflows
- Build multi-modal models
- Collaborate with Product Detection Engineering Customer Success
- Create streaming feature pipelines
- Design AI layer for autonomous detection
- Develop graph based reasoning engines
- Develop production large language models
- Develop tool-calling agents
- Experiment with retrieval-augmented generation
- Implement fallback strategies
- Manage prompt libraries and fine tuning
- Own evaluation and reliability
- Perform Red Team Testing
- Translate attacker behavior into ML and rule based detections
Perks/Benefits
Skills/Tech-stack
AWS | Agent systems | Cloud platform | Data Pipelines | Docker | Driven systems | Event Driven | Event Driven Systems | Fine Tuning | GRPC | Go | Google Cloud | Google Cloud Platform | Graph Databases | Java | Kubernetes | Langchain | Langgraph | Language Models | Large Language Models | Latency optimization | Microservices | Microsoft Azure | Multi-Agent | Multi-Agent Systems | Prompt engineering | Python | REST | Red team | Red team testing | Retrieval-Augmented Generation | Rust | Streaming Data | Streaming data pipelines | Tool-Calling
Education
Roles
AI | AI/ML Engineer | Engineer | Learning Engineer | ML Engineer | Machine Learning Engineer
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