Our Client, a multinational telecommunications technology company has an urgent and immediate need for an experienced Data Scientist with 5-8 years of experience in designing, developing, and deploying advanced machine learning and AI solutions.

We're seeking candidates with strong expertise in Large Language Models (LLMs), Natural Language Processing (NLP), and classical data science algorithms, along with hands-on experience building scalable data and AI pipelines in cloud-based environments.

Key Responsibilities:

- Design, develop, train, validate, and deploy machine learning and AI models, including LLM-based solutions.
- Build and optimize NLP applications leveraging transformer models and generative AI technologies.
- Perform LLM fine-tuning, prompt engineering, and model evaluation for domain-specific use cases.
- Develop scalable data processing and machine learning pipelines using PySpark/Spark and Databricks.
- Work with structured and unstructured datasets across SQL and NoSQL environments.
- Collaborate with data engineering and business teams to translate business requirements into AI/ML solutions.
- Conduct exploratory data analysis, feature engineering, and model performance tuning.
- Implement best practices for model governance, validation, monitoring, and lifecycle management.
- Utilize Azure Cloud services for data storage, model training, deployment, and orchestration.
- Create technical documentation and communicate findings to technical and non-technical stakeholders.

If you would like to learn more, please reach out to Elite Technical.

Required Skills

Required Skills:

- 5-8 years of experience in Data Science, Machine Learning, or AI Engineering roles.
- Strong experience with:
o Large Language Models (LLMs)
o Natural Language Processing (NLP)
o Classical Machine Learning/Data Science algorithms
- Hands-on experience in:
o Python
o PySpark / Apache Spark
o Databricks
o MongoDB or other NoSQL databases
o PostgreSQL and SQL development
o Azure Cloud platform
- Experience designing, training, validating, and deploying machine learning models.
- Knowledge of LLM fine-tuning techniques and model optimization.
- Strong understanding of data structures, algorithms, and statistical modeling concepts.
- Experience working with large-scale datasets and distributed computing frameworks.
- Strong analytical and problem-solving abilities
- Excellent communication and collaboration skills