1772 Fullstack IA Engineer Senior

Responsibilities

AI Solution Development

• Lead the design, development, and implementation of end-to-end, scalable AI solutions.
  
• Build, train, and optimize Machine Learning and Deep Learning models.
  
• Continuously improve model performance, accuracy, and operational cost efficiency.
  

Full Stack Engineering

• Develop and integrate backend and frontend components for AI-powered applications.
  
• Design scalable, secure, and high-performance software architectures.
  
• Ensure code quality through testing, code reviews, and software development best practices.
  

Data Science & Predictive Modeling

• Analyze large datasets to identify patterns and develop predictive models.
  
• Implement data preparation, cleansing, and transformation pipelines.
  
• Develop advanced analytics solutions to solve complex business challenges.
  

Cloud & MLOps

• Build and deploy AI solutions using Machine Learning services on AWS, Google Cloud Platform (GCP), or Microsoft Azure.
  
• Integrate AI models into scalable cloud infrastructures.
  
• Optimize model deployment, monitoring, maintenance, and lifecycle management in production environments.
  

Innovation & Technical Leadership

• Provide technical leadership for strategic Artificial Intelligence initiatives.
  
• Mentor and guide engineers across the team, promoting technical excellence and best practices.
  
• Research emerging AI technologies, tools, and industry trends to drive continuous innovation.
  

Documentation & Communication

• Document system architectures, technical processes, and design decisions.
  
• Communicate project progress, technical findings, and business impact effectively to both technical teams and business stakeholders.
  

Requisitos

Requirements

Required Qualifications

• 6-7 years of professional experience as a Full Stack Engineer.
  

• Advanced proficiency in Python.
  

• Strong experience with Java or Scala.
  

• Extensive experience designing and developing Artificial Intelligence solutions.
  

• Hands-on expertise with Machine Learning frameworks, including:
  

  • TensorFlow
    

  • PyTorch
    

• Experience using:
  

  • pandas
    

  • scikit-learn
    

• Experience working with cloud platforms, including:
  

  • Amazon Web Services (AWS)
    

  • Google Cloud Platform (GCP)
    

  • Microsoft Azure
    

• Knowledge of cloud-based Machine Learning services.
  

• Proven experience building advanced predictive models.
  

• Strong understanding of:
  

  • Software architecture
    

  • Scalable systems design
    

  • Data structures
    

  • Algorithms
    

• Proven experience developing Full Stack applications.