Linguistic Architect for Advanced Text Analysis
1 month ago
We are seeking a highly skilled Linguistic Architect to join our team at Unreal Gigs. This is an exceptional opportunity for an experienced NLP Engineer to design, develop, and deploy cutting-edge NLP models that transform text analysis and enhance our products.
As a key member of our engineering team, you will work closely with cross-functional teams to integrate NLP solutions into our applications. Your expertise in NLP techniques, machine learning, and deep learning will enable us to build innovative features like chatbots, voice assistants, and sentiment analysis.
Key Responsibilities:- NLP Model Development: Design and implement advanced NLP models using machine learning and deep learning techniques. You will work with architectures like transformers, RNNs, and BERT to develop models for text classification, named entity recognition, sentiment analysis, and language generation.
- Data Preprocessing and Feature Engineering: Preprocess and clean large textual datasets, converting unstructured data into structured formats suitable for model training. You will apply tokenization, stemming, lemmatization, and other NLP techniques to extract meaningful features from raw text.
- Model Training and Fine-Tuning: Train, fine-tune, and optimize pre-trained language models like GPT, BERT, and T5 on custom datasets. You will experiment with various model architectures and hyperparameters to improve accuracy, speed, and generalization.
- Model Deployment: Work with engineering teams to deploy NLP models into production environments. You will ensure models are scalable, efficient, and integrated seamlessly into applications such as chatbots, recommendation engines, or voice assistants.
- NLP Expertise: Strong knowledge of NLP techniques, including text classification, named entity recognition, sentiment analysis, and machine translation. Experience with pre-trained language models like BERT, GPT, RoBERTa, and T5.
- Programming and Tools: Proficiency in Python and experience with NLP libraries and frameworks like Hugging Face's Transformers, SpaCy, NLTK, or Stanford NLP. Ability to implement NLP models and algorithms using deep learning frameworks like TensorFlow or PyTorch.
- Text Preprocessing and Feature Engineering: Expertise in preprocessing raw text data, including tokenization, stemming, lemmatization, and vectorization (TF-IDF, word embeddings). Understanding of how to handle large-scale text data for NLP tasks.
- Model Deployment: Experience deploying NLP models in production environments using tools such as Docker, Kubernetes, or cloud-based services (AWS, Google Cloud, or Azure). Familiarity with API development and integration with web or mobile applications.
- Bachelor's or Master's degree in Computer Science, Computational Linguistics, AI, Machine Learning, or a related field. Equivalent experience in NLP engineering is also highly valued.
- Certifications or additional coursework in NLP, machine learning, or AI are a plus.
- 3+ years of experience in NLP engineering, with hands-on experience developing, training, and deploying NLP models in production environments.
- Proven experience working with large-scale textual datasets and applying machine learning or deep learning models to solve NLP challenges.
- $140,000 - $160,000 per year salary, depending on experience and qualifications.
- Comprehensive medical, dental, and vision insurance plans with low co-pays and premiums.
- Paid time off, flexible work schedules, and telecommuting options.
- Opportunities for professional development, training, and certification reimbursement.
- Access to wellness programs, including gym memberships, health screenings, and mental health resources.
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