Data Scientist
2 days ago
Role Overview
This Senior Developer position requires a seasoned professional to lead the development of innovative AI/ML systems. You will collaborate with cross-functional teams, leveraging your expertise in Python, deep learning frameworks, and software architecture to drive business value.
Main Responsibilities
- Drive the development of cutting-edge machine learning systems.
- Collaborate with cross-functional teams to deliver AI/ML projects.
- Leverage expertise in deep learning frameworks to build scalable AI solutions.
- Work closely with developers to ensure effective delivery of AI/ML projects.
- Implement data science processes to drive business value.
- Optimize SQL/NoSQL database performance.
- Design and implement Rest APIs and Python web frameworks.
- Debug and optimize code efficiency.
- Foster Agile/Scrum based software development lifecycle.
- Design, develop, and deploy AI models based on LLM and RAG.
Requirements
- 3-5 years of experience in Python development.
- 3-5 years of experience in Machine Learning/Deep Learning.
- Expertise in libraries like numpy, pandas, matplotlib, scikit-learn, spacy, nltk, transformers.
- Strong analytical and problem-solving skills.
- Knowledge of machine learning algorithms, deep learning algorithms, language models.
- NLP techniques for text representation, semantic extraction techniques, data structures, and modeling.
- Ability to design, develop, and deploy AI models, focusing on LLM and RAG.
- Effective software architecture design.
- Model training and evaluation experimentation.
- Statistical analysis of results and model refinement.
- Experience with deep learning frameworks like TensorFlow, Keras, PyTorch.
- Transformers architecture and various models.
- Multithreading and concurrency in Python.
- Deploying deep learning models into production.
- MLOps.
- Deep learning models' ability to handle multiple requests concurrently.
- Open-source Language Models.
- Python-based web frameworks like Django, Flask.
- Advanced SQL and NoSQL databases like PostgreSQL, MySQL, SQLite, MariaDB, MongoDB.
- GDPR compliance.
- Big data technologies and cloud platforms.
- Machine learning landscape updates.
- Software version control systems like Git, Bitbucket.
- Problem-solving and logical reasoning attitude.
- Teamwork and collaboration.
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