Machine Learning ( Generative AI & NLP ) Professional

Requirements:

-Total Experience 2+ Years

Strong expertise in Machine Learning, Generative AI fundamentals, and NLP fundamentals.

-Proven experience in building recommendation systems.

-Experience in developing and deploying applications with Large Language Models (LLMs) and Generative AI.

-Strong experience in ChatGPT, Generative AI, Prompt engineering & Data modelling.

-Hands on experience in NLTK, Machine Vision, Natural Language processing, Data Pipeline.

-Good knowledge in Video Analytics, Cloud architecture, Google BigQuery, Kubernetes.

Experience with cloud-based ML tools on AWS or Azure (e.g., Amazon SageMaker, Azure Machine Learning) and TensorRT/TFLite

-Proficiency in machine learning frameworks such as Keras, PyTorch, TensorFlow, and libraries like scikit-learn, pandas, and OpenCV.

-Expertise in data visualization using tools and libraries such as Matplotlib, Seaborn, or Plotly to effectively communicate insights.

-In-depth knowledge of mathematics, probability, statistics, and algorithms.

Solid understanding of data structures, data modeling, and software architecture.

-Proficiency in Python, with the ability to write robust and maintainable code.

-Familiarity with big data technologies like Hadoop, Spark, and distributed storage systems for large-scale data handling and parallel processing

Strong analytical and problem-solving skills with the ability to work independently and in collaborative teams.

-Excellent communication skills to articulate technical concepts and results effectively.

Responsibilities:

-Writing and reviewing great quality code

Understanding the client s business use cases and technical requirements and be able to convert them in to technical design which elegantly meets the requirements

-Mapping decisions with requirements and be able to translate the same to developers

-Identifying different solutions and being able to narrow down the best option that meets the client s requirements

Defining guidelines and benchmarks for NFR considerations during project implementation

-Writing and reviewing design document explaining overall architecture, framework, and high-level design of the application for the developers

-Reviewing architecture and design on various aspects like extensibility, scalability, security, design patterns, user experience, NFRs, etc., and ensure that all relevant best practices are followed

-Developing and designing the overall solution for defined functional and non-functional requirements; and defining technologies, patterns, and frameworks to materialize it

-Understanding and relating technology integration scenarios and applying these learnings in projects

-Resolving issues that are raised during code/review, through exhaustive systematic analysis of the root cause, and being able to justify the decision taken

- Carrying out POCs to make sure that suggested design/technologies meet the requirements

- Bachelor's or master's degree in computer science, Information Technology, or a related field.