C2 SMART AI Engineer
Tasks
- Apply model optimization techniques for latency memory and power constraints
- Build AI capabilities for digital agents and report processing
- Collaborate with product and UI UX on operator workflows and visualization
- Deliver end to end solutions with data scientists and DevSecOps
- Design edge vs core processing strategy for disconnected conditions
- Design fine tune and evaluate SLMs and DSLMs and selectively leverage LLMs
- Develop NLP pipelines for entity extraction intent recognition and normalization
- Enforce security controls guardrails and DoD compliance
- Extend text workflows to multimodal inputs image and speech
- Implement retrieval augmented generation grounded in authoritative doctrine
- Implement telemetry logging and real time monitoring with feedback loops
- Integrate AI services with secure APIs and messaging streams
- Orchestrate deploy version and manage models using Meibel
- Productionize models across edge on prem and cloud with CI CD
Perks/Benefits
- N/A
Skills/Tech-stack
API Design | CI/CD | Context understanding | Data Tagging | Deep learning | Edge Computing | Entity Extraction | Fine Tuning | GRPC | Generative AI | Intent Recognition | Kafka | Knowledge Distillation | Language Processing | Logging | Machine Learning | Message Streaming | Model Evaluation | Model Fine-tuning | Model Orchestration | Model Pruning | Model Quantization | Monitoring | Natural Language | Natural Language Processing | Neural Networks | ONNX | OpenVINO | REST | Retrieval-Augmented Generation | Secure APIs | Sequence Modeling | Sparse Neural Networks | Telemetry | TensorRT | Text Normalization | Tokenization | Zero Trust
Education
Roles
AI | AI Engineer | Engineer
Regions
Countries
States
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