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NLP Engineer
Data
Blazity

NLP Engineer

Blazity
3 990 - 5 730 USDNet/month - B2B
Type of work
Full-time
Experience
Mid
Employment Type
B2B
Operating mode
Remote

Tech stack

    NLP
    regular
    TensorFlow
    regular
    PyTorch
    regular
    Python
    regular
    unit tests
    regular
    Statistics
    regular
    Machine Learning
    regular
    transformers
    regular
    Deep Learning
    regular
    LLM Orchestration
    regular

Job description

We’re Blazity - a team of React.js and Next.js experts creating API first products.

We have years-long relationships with many of our clients. As trusted development partners, we take full ownership of the projects and continuously optimize apps, stores, websites, and implement new features, or automate workflows.

Looking for your next adventure? As it is said, you must gather your party before venturing forth - so why not join us? :)


We're looking for NLP Engineer.



As an NLP Engineer specialized in GPT-3 and GPT-4, you will be responsible for designing, developing, and maintaining natural language processing (NLP) systems and applications that leverage the capabilities of OpenAI's GPT-3 and GPT-4 models. Your primary focus will be on understanding the needs of the organization or clients and implementing NLP solutions using these state-of-the-art language models.

 

Responsibilities:

  • Model Development: Collaborate with researchers and data scientists to refine and improve GPT-3 and GPT-4 models by conducting experiments, fine-tuning, and testing. Stay updated with the latest research advancements in the field of NLP and apply them to enhance the performance and capabilities of the models.
  • System Integration: Integrate GPT-3 and GPT-4 models into existing or new applications and systems. Develop APIs and SDKs to provide seamless access to the language models for other developers or end-users. Optimize the integration process to ensure efficient utilization of resources.
  • Natural Language Understanding: Utilize GPT-3 and GPT-4 to build NLP systems that can comprehend and interpret human language in various domains. Develop algorithms and techniques for tasks such as sentiment analysis, entity recognition, intent detection, and text classification.
  • Text Generation: Leverage the generation capabilities of GPT-3 and GPT-4 to develop applications that can produce coherent and contextually relevant text. Implement techniques to control and fine-tune the generated output to meet specific requirements, such as generating personalized responses or adhering to a particular style or tone.
  • Performance Optimization: Continuously optimize the performance of NLP models and applications. Profile and analyze the computational and memory requirements of the models and implement optimizations to improve efficiency and reduce latency.
  • Data Processing and Cleaning: Preprocess and clean large volumes of text data to ensure high-quality input for the NLP models. Apply techniques such as tokenization, lemmatization, and data augmentation to improve the accuracy and robustness of the models.
  • Model Evaluation: Design and conduct experiments to evaluate the performance and effectiveness of GPT-3 and GPT-4 models for different NLP tasks. Develop evaluation metrics and benchmarks to measure and compare the performance of various models and techniques.
  • Documentation and Reporting: Document the design, development, and deployment processes of NLP systems and applications. Prepare reports and presentations to communicate findings, results, and recommendations to stakeholders, including management, researchers, and clients.


Requirements:

  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field. A Ph.D. is a plus.
  • English at C1 level
  • Strong understanding of natural language processing concepts, techniques, and algorithms.
  • Experience working with GPT-3 and/or GPT-4 models, including fine-tuning and evaluation.
  • Proficiency in programming languages such as Python, along with libraries and frameworks commonly used in NLP, such as TensorFlow, PyTorch, or spaCy.
  • Familiarity with deep learning architectures for NLP, including recurrent neural networks (RNNs), transformers, and attention mechanisms.
  • Knowledge of data preprocessing techniques and tools for NLP, such as tokenization, stemming, and named entity recognition.
  • Experience with large-scale data processing and distributed computing frameworks.
  • Strong analytical and problem-solving skills, with the ability to design and implement innovative solutions.
  • Excellent communication and collaboration skills to work effectively in cross-functional teams.


Our offer:

  • Enjoy 29 paid days off for B2B contractors
  • Comprehensive health and wellness coverage with Medicover and Multisport, fully sponsored by us
  • Flexible working hours
3 990 - 5 730 USD

B2B