Machine Learning Architect for Cloud-Based Solutions

hace 1 día


Madrid, Madrid, España LatamCent A tiempo completo
Job Summary

We are seeking a highly skilled Machine Learning Architect to lead the design, development, and deployment of cloud-based machine learning solutions. As a key member of our team, you will oversee the end-to-end machine learning lifecycle, including data preprocessing, model training, evaluation, and deployment.

About Us
At LatamCent, we are transforming the way companies develop breakthrough roadmaps leveraging Cloud-Based Technologies to boost efficiency, ensure compliance, deliver actionable insights and lower cost of total ownership.

Key Responsibilities:
  • Lead the design, development, and deployment of machine learning models and algorithms to solve complex business problems.
  • Oversee the end-to-end machine learning lifecycle, including data preprocessing, model training, evaluation, and deployment.
  • Utilize AWS SageMaker to build, train, and deploy machine learning models.
  • Leverage AWS Bedrock to develop robust and scalable generative AI solutions for various applications.
  • Develop and implement generative AI solutions to enhance business processes and customer experiences.
  • Implement MLOps practices, including model monitoring, and automation of the training and deployment pipeline.
  • Collaborate with cross-functional teams to integrate ML models into production environments and applications.
  • Provide technical leadership and mentorship to a team of data scientists and machine learning engineers.
  • Communicate complex machine learning concepts and insights to non-technical stakeholders.
  • Ensure the integrity and quality of data throughout the machine learning pipeline.
  • Stay current with the latest advancements in machine learning, AI, and AWS technologies to continuously improve capabilities.

Requirements:
  • Minimum of 7 years of hands-on experience in machine learning and data science roles, with significant experience in leading and managing ML projects.
  • Proven track record of successfully delivering end-to-end machine learning solutions from concept to production deployment.
  • Extensive expertise in AWS services such as SageMaker, AWS Bedrock, and other AI/ML tools.
  • Strong proficiency in Python and familiarity with machine learning libraries such as TensorFlow, PyTorch, and Scikit-Learn.
  • Experience with MLOps practices, including model monitoring, deployment automation, and CI/CD pipelines.
  • Demonstrated ability to design and implement scalable and efficient machine learning architectures in cloud environments.
  • Deep understanding of data engineering, feature engineering, and data preprocessing techniques.
  • Experience with AutoML, hyperparameter tuning, and model optimization techniques.
  • Leadership skills with the ability to lead and mentor a team of data scientists and machine learning engineers effectively.

What We Offer:
  • $4000 USD monthly salary.
  • Full-time remote work flexibility.
  • Opportunity for professional growth.


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