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 ensuring 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.

Must-Have Skills

• Machine Learning – 5 years
• Natural Language Processing – 2 years
• Docker – 2 years
• Python – 3 years
• TensorFlow – 2 years
• Pytorch – 2 years
• Deep Learning – 2 years

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 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, and 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.