Principal AI/ML Engineer (Large Language Model)
Tasks
- Analyze multi domain datasets to extract features and build models
- Apply large language models to remote sensing applications
- Build applications with LLM frameworks
- Communicate technical status to leadership
- Deploy LLM solutions with Kubernetes
- Fine tune foundation models and build adapters
- Implement Retrieval-Augmented Generation with vector databases
- Lead and mentor interdisciplinary team to implement machine learning algorithms
- Review research publications to apply cutting edge concepts
Perks/Benefits
Skills/Tech-stack
AWS | Adversarial Networks | BERT | CUDA | CUDA programming | Computer Vision | Cuda libraries | Deep learning | Docker | Dspy | EC2 | Faster R-CNN | Fine Tuning | GPU | GPU Computing | Generative Adversarial Networks | Gymnasium | Huggingface | Keras | Kubernetes | Lambda | Langchain | Language Models | Language Processing | Large Language Models | Linux | Machine Learning | Natural Language | Natural Language Processing | NumPy | Object Detection | OpenCV | PEFT | Pandas | Pinecone | Podman | Polars | Prompt engineering | PyTorch | Python | R-CNN | Reinforcement Learning | Retrieval-Augmented Generation | Rllib | S3 | Scikit-learn | Stable Baselines | TensorFlow | Transformers | Variational Autoencoders | Vector Databases | Weaviate | YOLO
Education
Roles
AI/ML Engineer | Engineer | ML Engineer | Principal | Principal AI/ML Engineer
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