NLP AI Engineer
Tasks
- Build dataset and synthetic data pipelines
- Collaborate with research, engineering, product teams
- Create evaluation frameworks and benchmarking
- Deploy and serve production AI models
- Design fine tune optimize large language models
- Develop distributed training pipelines
- Establish automated safety testing hallucination detection
- Evaluate NLP research foundation models frameworks
- Implement retrieval-augmented generation pipelines
- Lead architecture reviews and best practices
- Mentor junior AI engineers
- Optimize training and inference performance
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Cloud platform | Deep learning | DeepSpeed ZeRO | Direct Preference Optimization | Distributed Training | Docker | Embeddings | Experiment tracking | FSDP | Fine Tuning | Google Cloud | Google Cloud Platform | Hallucination detection | Knowledge Base | Knowledge graphs | Kubernetes | Language Models | Language Processing | Large Language Models | LoRA | MLOps | Machine Learning | Microsoft Azure | Model Evaluation | Model Parallelism | Model Serving | Natural Language | Natural Language Processing | PEFT | PPO | Pipeline parallelism | Preference optimization | PyTorch | Python | QLoRA | RAG | RLHF | Ray | Reinforcement Learning | Responsible AI | Retrieval-Augmented Generation | Safety testing | Supervised Fine Tuning | Tensor Parallelism | Transformers | Vector Databases | Vector Search
Education
Roles
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