Natural Language Processing (NLP) Specialist (The Language Architect)

Are you fascinated by the potential of language and how it can be transformed into intelligent systems? Do you love working with cutting-edge Natural Language Processing (NLP) techniques to help machines understand and generate human language? If you're passionate about building NLP solutions that solve real-world problems, then our client has an exciting opportunity for you. We’re looking for a Natural Language Processing (NLP) Specialist (aka The Language Architect) to design and develop sophisticated language models and applications that drive innovation and transform how businesses interact with text and speech data.

As an NLP Specialist at our client, you’ll work closely with AI researchers, data scientists, and software engineers to design and deploy NLP systems that power a range of applications, from chatbots and voice assistants to sentiment analysis and text mining. Your expertise will play a critical role in making human-machine communication seamless, intuitive, and effective.

Key Responsibilities:

1. Develop NLP Models and Algorithms:
• Design and implement state-of-the-art NLP models, such as transformers, BERT, GPT, and other neural network architectures, to solve language-based problems. You’ll work on tasks like sentiment analysis, text generation, named entity recognition, and machine translation.
2. Build NLP-Powered Applications:
• Develop NLP applications that enable chatbots, voice assistants, and other AI-driven tools to understand and generate natural language. You’ll help create intuitive user experiences by making these systems more conversational and context-aware.
3. Data Preprocessing and Text Mining:
• Perform data preprocessing and feature extraction on large text datasets to prepare them for NLP tasks. You’ll clean, tokenize, and transform text data, ensuring that it’s optimized for language models and machine learning algorithms.
4. Experiment with Cutting-Edge NLP Techniques:
• Stay up-to-date with the latest advancements in NLP research, including developments in deep learning and transfer learning. You’ll experiment with new algorithms and approaches to improve the performance of NLP models and push the boundaries of what's possible.
5. Deploy Models into Production:
• Work with engineering and DevOps teams to deploy NLP models into production environments, ensuring they are scalable, efficient, and reliable. You’ll use cloud platforms and AI services to implement and monitor models in real-world applications.
6. Collaborate with Cross-Functional Teams:
• Partner with data scientists, product managers, and engineers to integrate NLP models into products and services. You’ll help translate business objectives into NLP solutions that drive user engagement and improve business outcomes.
7. Monitor and Fine-Tune Model Performance:
• Continuously monitor the performance of deployed models, fine-tuning them as needed to ensure they deliver accurate and relevant results. You’ll retrain models using new data and feedback to keep them up-to-date and robust.

Requirements

Required Skills:

• NLP Expertise: Strong experience in natural language processing techniques, including sentiment analysis, named entity recognition, text classification, and machine translation. You’re familiar with neural network models like transformers, RNNs, and CNNs.
• Machine Learning and Deep Learning: Proficiency in machine learning and deep learning frameworks like TensorFlow, PyTorch, or Hugging Face. You know how to apply these frameworks to build, train, and fine-tune NLP models.
• Programming and Data Skills: Proficiency in Python and experience working with NLP libraries such as NLTK, SpaCy, or Stanford NLP. You’re skilled at manipulating large text datasets and preparing them for analysis and model training.
• Model Deployment and Optimization: Experience deploying NLP models into production environments using cloud platforms (AWS, GCP, Azure) and containerization tools like Docker. You know how to optimize models for scalability and performance.
• Collaboration and Communication: Strong collaboration skills, with the ability to work with cross-functional teams and communicate complex technical concepts to non-technical stakeholders.

Educational Requirements:

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, Linguistics, or a related field. Equivalent experience in NLP or machine learning is highly valued.
• Certifications or additional coursework in NLP, AI, or deep learning are a plus.

Experience Requirements:

• 3+ years of experience in NLP or machine learning, with hands-on experience building and deploying NLP models in real-world applications.
• Proven track record of working with large text datasets, developing language models, and delivering NLP-driven solutions that solve business problems.
• Experience with cloud-based NLP services (AWS Comprehend, Google Cloud NLP, Azure Cognitive Services) is highly desirable.

Benefits

• Health and Wellness: Comprehensive medical, dental, and vision insurance plans with low co-pays and premiums.
• Paid Time Off: Competitive vacation, sick leave, and 20 paid holidays per year.
• Work-Life Balance: Flexible work schedules and telecommuting options.
• Professional Development: Opportunities for training, certification reimbursement, and career advancement programs.
• Wellness Programs: Access to wellness programs, including gym memberships, health screenings, and mental health resources.
• Life and Disability Insurance: Life insurance and short-term/long-term disability coverage.
• Employee Assistance Program (EAP): Confidential counseling and support services for personal and professional challenges.
• Tuition Reimbursement: Financial assistance for continuing education and professional development.
• Community Engagement: Opportunities to participate in community service and volunteer activities.
• Recognition Programs: Employee recognition programs to celebrate achievements and milestones.