AI/ML Engineer

Role:AI/ML Engineer
Location: Charlotte, NC (Onsite)
Visa: Any

Responsibilities:
·       Design, train, and optimize small- to medium-scale NLP models for token or entity classification tasks.
·       Develop data processing, labeling, and evaluation pipelines using Python, Pandas, and PyTorch.
·       Apply model compression, quantization, pruning, and distillation techniques to enhance model efficiency.
·       Experiment with embeddings, sequence labeling architectures (e.g., BiLSTM-CRF, CNN-RNN hybrids), and attention-based mechanisms within non-LLM frameworks.
·       Build reproducible training workflows, conduct error analysis, and iterate model improvements based on metrics and qualitative feedback.
·       Collaborate with engineering and product teams to deploy and monitor models in production environments.

Required Qualifications
·       M.S. in Computer Science, Data Science, Computational Linguistics, or a related field.
·       4+ years of experience in NLP or machine learning model development.
·       Proficiency in PyTorch (model architecture design, training loops, custom loss functions).
·       Strong command of Python data stack (Pandas, NumPy, scikit-learn).
·       Demonstrated experience optimizing small models (<300M parameters) for accuracy, speed, or cost.
·       Solid understanding of token classification tasks, sequence labeling, and evaluation metrics (precision, recall, F1).

Preferred Qualifications (Nice-to-Have)
·       Experience with the Flair NLP framework for sequence labeling and embedding management.
·       Familiarity with CRF, BiLSTM, and other traditional NLP architectures.
·       Hands-on experience with model compression, knowledge distillation, or edge deployment.
·       Prior contributions to open-source NLP projects or small-model benchmarks.
·       Understanding of MLOps and deployment workflows (e.g., ONNX, TorchScript, Docker).