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.