Day-to-day Responsibilities:
- Designing and Building machine learning systems based on business requirements and objectives.
- Research and implement appropriate ML algorithms and tools
- Perform exploratory data analysis to identify patterns, trends, and correlations in large datasets.
- Solving complex problems and comparing alternative solutions, trade-offs, and diverse points of view to determine a path forward.
- Responsible for deploying and managing machine learning models in production and ensure their scalability and efficiency.
- Training and testing ML models at scale in the cloud.
- Monitor and evaluate model performance, making necessary adjustments to improve accuracy and efficiency.
- Stay updated with the latest developments in machine learning and AI to bring innovative solutions to the team.
Skills And Qualifications
- 5+ years of experience implementing and deploying machine learning and deep learning frameworks.
- Strong proficiency in Python and deep learning frameworks such as TensorFlow, PyTorch, or Keras
- Experience in productionizing ML Models
- Experience with natural language processing (NLP) algorithm
- Experience with containerization technologies (e.g., Docker)
- Solid understanding of statistical methods and data analysis
- Solid understanding of LLMs, Prompt Engineering, RAG, GraphRAG, Langchain frameworks.
- Solid understanding of machine learning algorithms, data structures, and software engineering principles.
- Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure) and their ML services
- Experience with version control systems like Git, Bitbucket etc
- Ability to work independently and proactively find solutions to challenges.
- Ability to collaborate effectively with team members and stakeholders.
