Lead AI ML Engineer

2 months ago

India Programmers.io Full time

Job Description:

Job Title: Senior .Machine Learning Engineer/ Lead

Shift Timings: should be available to work till 9:00-9:30 PM IST

Location: Remote

Experience required: 7 to 10 years

We are seeking a talented and experienced Machine Learning Engineer , specializing in developing and deploying machine learning models for Natural Language Processing (NLP), forecasting, and leveraging OpenAI's technologies. In this role, you will be responsible for designing, implementing, and optimizing machine learning algorithms to tackle challenging problems in the domains of NLP, Computer Vision, and Forecasting models.

Key Responsibilities:

  1. Develop and deploy state-of-the-art machine learning models for Natural Language Processing (NLP) tasks, including sentiment analysis, named entity recognition, text classification, and language generation.
  2. Utilize OpenAI's cutting-edge technologies and APIs to enhance NLP capabilities and develop innovative solutions for text-based applications.
  3. Design and implement machine learning models for business forecasting and financial time series analysis, leveraging techniques such as time series forecasting, statistical modelling, and deep learning.
  4. Conduct thorough data analysis and preprocessing to extract relevant features and optimize model performance for business forecasting tasks.
  5. Collaborate closely with data scientists, software engineers, and domain experts to understand business requirements and translate them into actionable machine learning solutions.
  6. Stay updated with the latest advancements in machine learning research, particularly in the areas of NLP, time series analysis, and forecasting, and integrate them into existing projects to improve model accuracy and efficiency.
  7. Deploy machine learning models into production environments and monitor their performance, ensuring scalability, reliability, and efficiency.
  8. Contribute to the development of internal tools, libraries, and best practices to streamline the machine learning workflow and foster collaboration across teams.

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