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ML Architect

2 months ago

Bengaluru, India First American (India) Full time

A Machine Learning Architect is a professional who designs, develops, and implements machine learning models, systems, and solutions for various business problems. Their primary responsibility is to architect and build scalable, efficient, and robust machine learning infrastructures that can handle large volumes of data and deliver accurate predictions. They often work closely with data scientists, data engineers, and other stakeholders to ensure that machine learning models are effectively integrated into the organization's products and services.


Key job responsibilities of a Machine Learning Architect may include:


  • Collaborate with cross-functional teams to understand business requirements and identify appropriate machine learning solutions.
  • Design, develop, and implement end-to-end machine learning architectures that can process large volumes of data in real-time.
  • Evaluate and select machine learning algorithms, tools, and frameworks based on the specific needs of the organization.
  • Develop and maintain scalable and efficient data pipelines to gather, preprocess, and clean data for machine learning models.
  • Create and optimize machine learning models using various techniques such as feature selection, dimensionality reduction, and hyperparameter tuning.
  • Ensure the proper deployment, monitoring, and maintenance of machine learning models in production environments.
  • Evaluate the performance of machine learning models and make necessary adjustments to improve their accuracy and efficiency.
  • Keep up-to-date with the latest advancements in machine learning, artificial intelligence, and related technologies to ensure the organization remains competitive.
  • Mentor and provide guidance to data scientists, engineers, and other team members in the development and implementation of machine learning models.
  • Present and communicate machine learning solutions to stakeholders, including non-technical audiences, to ensure understanding and support for the project.
  • Presenting results in a clear manner
  • Propose solutions and strategies to tackle business challenges
  • Collaborate with Business and IT teams
  • Setting up ML Ops to run the ML solution from development up to deployment



Required skills and qualifications:


  • Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field, with a strong focus on machine learning and artificial intelligence.
  • Extensive experience in designing, building, and deploying machine learning models and systems.
  • Proficiency in programming languages such as Python, R, or Java, and machine learning libraries and frameworks like TensorFlow, PyTorch, or Scikit-learn.
  • Knowledge and working experience in Open Ai
  • Knowledge of data manipulation, preprocessing, and feature engineering techniques.
  • Strong understanding of various machine learning algorithms, including supervised and unsupervised learning methods, and their applications.
  • Familiarity with cloud computing platforms such as AWS, Azure, or Google Cloud, and their machine learning services.
  • Excellent problem-solving, analytical, and critical thinking skills.
  • Strong communication and collaboration skills, with the ability to work effectively with diverse teams and explain complex concepts to non-technical stakeholders.
  • Continuous learning mindset and staying current with the latest trends and advancements in the field of machine learning and artificial intelligence.


Educational Qualification:



Minimum of 15 years of formal education - Graduate / Post Graduate degree (or equivalent) in Computer Science / Information Technology/Engineering or related area of expertise.