NLP Data Scientist

Role & responsibilities

• Design, develop, and optimize NLP models for applications like chatbots, virtual

assistants, and text analytics.

• Develop and implement Generative AI models and algorithms using advanced

techniques such as GPT, Variational Autoencoders (VAE), and Generative

Adversarial Networks (GANs).

• Conduct research to stay current with the latest advancements in Generative AI,

Machine Learning (ML), and Deep Learning (DL) and identify opportunities to

integrate them into our products and services.

• Fine-tune and deploy pre-trained models (e.g., GPT, BERT, T5) for specific tasks.
• Build and maintain data pipelines for preprocessing, feature extraction, and model

evaluation.

• Develop clear and concise documentation, including technical specifications, user

guides, and presentations, to communicate complex AI concepts to both technical

and non-technical stakeholders.

• Collaborate with cross-functional teams to design AI-driven solutions that meet

business objectives.

• Contribute to the establishment of best practices and standards for generative AI

development within the organisation.

• Provide technical mentorship and guidance to junior team members.
• Ensure scalability and robustness of deployed models in production environments.

Preferred candidate profile

Technical Skills

• Expertise in Machine Learning (ML), Deep Learning (DL), and Natural Language

Processing (NLP).

• Proficiency in developing and implementing Generative AI techniques such as

RAGs, GPT, VAE, and GANs.

• Strong programming skills in Python, with experience in frameworks like PyTorch or

TensorFlow.

• Familiarity with NLP libraries (Hugging Face, SpaCy, NLTK) and GenAI tools.
• Knowledge of cloud platforms (AWS, Azure, GCP) and MLOps practices.
• Experience with vector databases like FAISS or Pinecone.
• Strong understanding of algorithms, data structures, and optimization techniques.

Soft Skills

• Excellent research and analytical skills.
• Strong written and verbal communication skills to explain complex AI concepts

effectively.

• Ability to work collaboratively in a team environment.

Educational Background

• Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data

Science, or a related field.

Preferred Qualifications

• Hands-on experience with large-scale language models, fine-tuning, and prompt

engineering.

• Familiarity with MLOps tools such as Docker, Kubernetes, and CI/CD pipelines.
• Exposure to real-time NLP applications like voice assistants and TTS systems.
• Proven track record of developing innovative AI solutions in production environments.

Perks and benefits

• Be part of a team at the forefront of NLP and Generative AI innovation.
• Competitive salary and benefits package.
• Opportunities for professional growth and technical mentorship.
• Flexibility in working arrangements and the chance to impact real-world AI solutions.