Distinguished Artificial Intelligence Professional

6 days ago

Nellore, Andhra Pradesh, India beBeeMachineLearning Full time ₹ 2,00,00,000 - ₹ 3,00,00,000

**Job Title:** Senior Machine Learning Engineer

Job Description

We are revolutionizing ground transportation services globally by empowering local fleets. Our mission is to provide high-quality services.

  • Design and implement cutting-edge machine learning models using Python, SQL, and relevant tools to drive business growth.
  • Collaborate with cross-functional teams to identify opportunities for applying machine learning techniques to complex problems.
  • Conduct research and experimentation to explore new machine learning approaches and technologies.
  • Optimize existing machine learning models for improved performance and efficiency.
  • Provide technical leadership and mentorship to junior team members.
Required Skills and Qualifications

Strong background in machine learning, natural language processing, artificial intelligence, predictive modeling, and statistical modeling.

  • In-depth knowledge of reinforcement learning algorithms (e.g., DQN, PPO, Actor-Critic) with hands-on project experience.
  • Proven experience in time series forecasting methods (e.g., ARIMA, LSTM, Prophet) and their practical application.
  • Proficient in Python, SQL, and other relevant programming languages.
  • Familiarity with cloud computing platforms such as AWS or Azure is a plus.
  • Ability to work collaboratively in a dynamic environment and communicate effectively with stakeholders at all levels of the organization.
  • Bachelor's or master's degree in computer science, mathematics, statistics, or related field with a minimum of 5 years of experience.

Preferred Qualifications:

  • Expertise in Python with the ability to write performant production-quality code, familiarity with SQL.
  • Experience building and operating large-scale distributed systems using Amazon Web Services (S3, Kinesis, CloudFormation, EKS, AWS Security and Networking).
  • Experience with distributed large-scale data processing.
  • Basic understanding of the machine learning project lifecycle.
  • Experience building and scaling machine learning models using large amounts of data.

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