Job description
Responsibilities
AI Solution Development
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Lead the design, development, and implementation of end-to-end, scalable AI solutions.
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Build, train, and optimize Machine Learning and Deep Learning models.
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Continuously improve model performance, accuracy, and operational cost efficiency.
Full Stack Engineering
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Develop and integrate backend and frontend components for AI-powered applications.
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Design scalable, secure, and high-performance software architectures.
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Ensure code quality through testing, code reviews, and software development best practices.
Data Science & Predictive Modeling
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Analyze large datasets to identify patterns and develop predictive models.
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Implement data preparation, cleansing, and transformation pipelines.
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Develop advanced analytics solutions to solve complex business challenges.
Cloud & MLOps
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Build and deploy AI solutions using Machine Learning services on AWS, Google Cloud Platform (GCP), or Microsoft Azure.
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Integrate AI models into scalable cloud infrastructures.
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Optimize model deployment, monitoring, maintenance, and lifecycle management in production environments.
Innovation & Technical Leadership
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Provide technical leadership for strategic Artificial Intelligence initiatives.
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Mentor and guide engineers across the team, promoting technical excellence and best practices.
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Research emerging AI technologies, tools, and industry trends to drive continuous innovation.
Documentation & Communication
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Document system architectures, technical processes, and design decisions.
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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.