Data Scientist /Machine Learning Engineer @ Hitachi Vantara

The Role

We are looking for a skilled Data Scientist/ML Engineer with a good background in statistical and machine learning methods, with a specialized focus on natural language processing (NLP).

The ideal candidate needs to have good knowledge of model training, retraining and optimization and will proactively collaborate in productionising end-to-end machine learning solutions at scale.

What youll bring

Understand business and product needs and use classical ML methods or advanced AI techniques to solve them at scale
Design, train, and fine-tune machine learning models for information extraction (PII extraction), and evaluate model performance using relevant metrics and iteratively improve the models.
Communicate and collaborate with engineering/cross-functional teams to implement a feedback mechanism to optimise the models by training, tuning and evaluating them on a timely basis
What you will need:
Bachelors Degree in Engineering or equivalent, with 5-8 years of experience in solving industry problems using statistical, traditional ML and AI methods with proven experience in developing machine learning or NLP models, particularly for information extraction tasks
Enthusiastic learner and skilled in both theory and practice of basic statistical methods such as regression, clustering, general ML algorithms such as SVM, tree-based methods, neural networks etc. for solving supervised and unsupervised problems.
Experience working on advanced NLP methods like feature extraction, tagging and entity recognition and classification to identify sensitive information that comply with relevant data privacy regulations from structured and unstructured data sources.
Understanding of data privacy regulations and best practices.
Good Understanding of evaluation metrics specific to NLP tasks.
Skills in working with LLMs through prompt engineering, fine-tuning pre-trained models on specific datasets for targeted applications, etc would be good to have
Work closely with data engineers, software developers, and other stakeholders to integrate the solutions into existing systems with systemic feedback and continuous training and optimization.

Technical Skills:
Proficiency in programming languages such as Python
Experience with machine learning frameworks (e.g., Sklearn, TensorFlow, PyTorch).
Experience with NLP libraries and frameworks (e.g., spaCy, NLTK, Hugging Face Transformers).
Good to have: Familiarity with libraries and frameworks commonly used for LLMs (e.g., Hugging Face Transformers, LlamaIndex, LangChain etc).