Ai Ml Engineer

Job Title: AI/ML Engineer

Job Type:

About the Role:

AI/ML Engineer

The ideal candidate will have a deep understanding of machine learning, data modeling, and AI technologies, along with experience in building end-to-end solutions. You should be passionate about solving complex problems, driving innovation, and working in a collaborative environment.

Responsibilities:

• Design, develop, and deploy machine learning models for predictive analytics, automation, and optimization.
  
• Build and maintain data pipelines for AI applications, ensuring that data is clean, reliable, and ready for analysis.
  
• Apply advanced AI/ML techniques such as

  deep learning

  ,

  reinforcement learning

  , and

  natural language processing (NLP)

  to solve real-world problems.
• Collaborate with data scientists and software engineers to integrate AI models into production systems and applications.
  
• Perform exploratory data analysis (EDA) and feature engineering to identify meaningful patterns and insights from large datasets.
  
• Optimize model performance and scalability through techniques such as hyperparameter tuning, parallel processing, and cloud-based model deployment.
  
• Contribute to the development of AI/ML frameworks and tools to improve the efficiency and effectiveness of the team.
  
• Stay up to date with the latest trends, research, and advancements in AI/ML technologies.
  
• Mentor junior engineers and support their growth in the AI/ML domain.
  
• Communicate technical findings and results to both technical and non-technical stakeholders.
  

Requirements:

• 4-10 years of experience in

  AI/ML

  engineering or related fields.
• Strong proficiency in

  Python

  and machine learning frameworks (e.g.,

  TensorFlow

  ,

  PyTorch

  ,

  Keras

  ,

  Scikit-learn

  ).
• Solid understanding of machine learning algorithms,

  deep learning

  ,

  NLP

  , and

  reinforcement learning

  .
• Experience with data preprocessing, feature engineering, and working with large datasets.
  
• Hands-on experience with cloud platforms (e.g.,

  AWS

  ,

  Azure

  ,

  Google Cloud

  ) for model deployment and management.
• Proficiency in

  SQL

  and experience with

  NoSQL

  databases for data retrieval.
• Knowledge of model evaluation metrics, cross-validation, and performance optimization techniques.
  
• Familiarity with

  CI/CD

  pipelines for deploying machine learning models.
• Experience with

  data visualization

  and communication of results to stakeholders.
• Strong problem-solving abilities and a passion for working on complex AI challenges.
  
• Ability to work independently as well as collaborate effectively in a team environment.