Machine Learning Solutions Architect

Há 3 dias


São Paulo, São Paulo, Brasil LatamCent Tempo inteiro
Overview
SOURCEFUSE is a pioneering technology company that specializes in transforming businesses through cloud-based technologies. Our mission is to deliver cutting-edge solutions that drive efficiency, compliance, and actionable insights.

Job Description:
We are seeking an experienced Machine Learning Solutions Architect to lead our team of data scientists and machine learning engineers. The ideal candidate will have a strong background in machine learning, with expertise in AWS SageMaker, AWS Bedrock, and generative AI solutions. This role involves designing, developing, and deploying advanced ML models to solve complex business problems.

Main Responsibilities:
  1. Design, develop, and deploy machine learning models and algorithms to address intricate business challenges.
  2. Oversee the entire machine learning lifecycle, encompassing data preprocessing, model training, evaluation, and deployment.
  3. Leverage AWS SageMaker to build, train, and deploy machine learning models.
  4. Utilize AWS Bedrock to create robust and scalable generative AI solutions for various applications.
  5. Develop and implement generative AI solutions to enhance business processes and customer experiences.
  6. Implement MLOps practices, including model monitoring, and automation of the training and deployment pipeline.
  7. Collaborate with cross-functional teams to integrate ML models into production environments and applications.
  8. Provide technical leadership and mentorship to a team of data scientists and machine learning engineers.
  9. Communicate complex machine learning concepts and insights to non-technical stakeholders.
  10. Ensure the integrity and quality of data throughout the machine learning pipeline.

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

What You'll Get:
  • $4,000 USD monthly salary.
  • Full-time remote work flexibility.
  • Opportunity for professional growth and development.


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