AI Engineer
Tasks
- Build context engines
- Build knowledge bases
- Build multi agent planning
- Build recommendation models
- Compress models
- Containerize ML workloads
- Deploy models on edge devices
- Design agent orchestration
- Develop AI guardrails
- Distill knowledge
- Evaluate model quality
- Fine-tune LLMs
- Implement MLOps
- Implement RAG
- Implement agent memory
- Implement function calling
- Implement model serving
- Manage multi domain routing
- Monitor production models
- Optimize on device inference
- Prune models
- Quantize models
- Research LLMs
- Resolve task conflicts
Perks/Benefits
- N/A
Skills/Tech-stack
Agent Orchestration | Agent systems | Automatic Speech Recognition | Automotive Domain | Computer Vision | Containerization | Context engineering | DPO | Fine Tuning | Function Calling | Hugging Face | Hugging Face Transformers | Knowledge Distillation | LLMOps | Language Models | Large Language Models | LoRA | MLOps | Memory | Model Compression | Model Serving | Monitoring | Multi-Agent | Multi-Agent Systems | ONNX | ONNX Runtime | Object Detection | On-device Inference | PEFT | Planning | Prompt engineering | Pruning | PyTorch | Python | Quantization | RAG | RLHF | Retrieval-Augmented Generation | Speech Recognition | TFLite | TensorRT | Text to Speech | Tool use | Transformer | VLLM | Video Understanding | Voice Cloning | Wake Word | Wake word detection
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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