NLP AI Engineer
New
J
JobgetherArtificial Intelligence
Based in United StatesFull-TimeSenior
Salary130,000 - 180,000 USD per year
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Job Details
- Experience
- 10+ years
- Required Skills
- AWSPythonPyTorchAzureNLPLLMMLOps
Requirements
- Master's or Ph.D. in Computer Science, AI, Machine Learning, NLP, or a related technical discipline, or equivalent professional experience.
- 10+ years of professional experience in Artificial Intelligence, Machine Learning, NLP, or LLM engineering.
- Expert-level Python programming skills with extensive experience using PyTorch and transformer-based architectures.
- Proven experience fine-tuning and deploying large language models in production environments.
- Strong expertise in distributed training technologies such as FSDP, DeepSpeed ZeRO, pipeline parallelism, tensor parallelism, and model parallelism.
- Hands-on experience with RLHF, DPO, PPO, or other preference optimization techniques.
- Experience using AWS, Microsoft Azure, or Google Cloud Platform for AI and machine learning workloads.
- Strong understanding of machine learning algorithms, deep learning, NLP, model evaluation, and MLOps practices.
- Excellent analytical, communication, collaboration, and technical leadership skills.
Responsibilities
- Design, fine-tune, optimize, and deploy large language models using SFT, LoRA, QLoRA, RLHF, DPO, PPO, PEFT, and related techniques.
- Architect scalable distributed training pipelines using modern deep learning frameworks and GPU clusters.
- Develop high-quality datasets, synthetic data generation pipelines, and evaluation frameworks to improve model accuracy, robustness, and reliability.
- Optimize large-scale GPU training, inference performance, experiment tracking, and model-serving infrastructure.
- Design and implement Retrieval-Augmented Generation (RAG) pipelines, embedding models, vector search systems, and agentic AI workflows.
- Develop automated benchmarking, safety testing, hallucination detection, and Responsible AI evaluation frameworks.
- Collaborate with AI researchers, software engineers, data scientists, and product teams to deliver production-ready enterprise AI applications.
- Lead architecture reviews and establish best practices for LLM development, deployment, and operational excellence.
- Mentor junior AI engineers and contribute to technical leadership across AI engineering initiatives.
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