Data Scientist
First seen by Alion on Sep 17, 2026.
We are looking for an experienced GenAI Data Scientist to design, develop, and deploy machine learning and Generative AI solutions across NLP and large-scale data environments. The role requires strong hands-on expertise in machine learning, NLP, LLMs, GenAI application development, and scalable data pipelines, with the ability to take models and AI solutions from experimentation through production.
Key Responsibilities :
- Design, develop, and deploy machine learning and Generative AI solutions for business and product use cases.
- Develop NLP and LLM-based solutions including text classification, information extraction, semantic search, summarization, question answering, and conversational AI.
- Work with LLMs, prompt engineering, embeddings, vector search, RAG, and LLM-based application architectures.
- Develop and evaluate AI solutions using appropriate model evaluation methodologies, datasets, and performance metrics.
- Build and optimize scalable data pipelines supporting ML model development, training, inference, and production workloads.
- Design pipelines with appropriate considerations for data volumes, SLAs, latency, freshness, backfill, data quality, and failure handling.
- Perform data preparation, feature engineering, experimentation, and statistical analysis to support machine learning solutions.
- Work with structured and unstructured data to develop high-quality datasets for ML and GenAI applications.
- Develop, test, and optimize machine learning models using appropriate frameworks and libraries.
- Collaborate with Data Engineers, Software Engineers, Product teams, and business stakeholders to translate requirements into production-ready AI solutions.
- Monitor model and pipeline performance and troubleshoot data, model, and production issues.
- Implement appropriate practices for model versioning, experimentation, reproducibility, and deployment.
- Stay current with developments in Generative AI, NLP, LLMs, machine learning frameworks, and AI engineering practices.
Requirements :
- 7 - 12 years of experience in Data Science, Machine Learning, NLP, or related fields, with hands-on experience in Generative AI/LLM solutions.
- Strong understanding of machine learning algorithms, statistical modelling, and data science methodologies.
- Strong hands-on experience in NLP and ML systems.
- Practical experience working with LLMs, Generative AI, prompt engineering, embeddings, RAG, vector databases, or related technologies.
- Strong programming skills in Python and experience with relevant ML/data science libraries and frameworks.
- Hands-on experience designing and delivering scalable data pipelines for ML or analytics workloads.
- Strong understanding of data processing, data quality, transformation, and pipeline reliability.
- Experience working with ML frameworks such as PyTorch, TensorFlow, Scikit-learn, Hugging Face, or equivalent.
- Experience with distributed data processing or data engineering technologies such as Spark, Databricks, Kafka, Airflow, or equivalent would be an advantage.
- Experience taking ML/GenAI solutions from experimentation/PoC to production.
- Strong analytical, problem-solving, communication, and cross-functional collaboration skills.
Skills
Data Science, Data Scientist, Generative AI, NLP, Machine Learning, Artificial Intelligence, Conversational AI, Statistical Modeling, Python, PyTorch