As an AI Data Engineer, you will play a crucial role in designing and building scalable data pipelines, infrastructure, and machine learning systems to support AI-driven projects. You will collaborate closely with AI Product Managers, Data Scientists, and Software Engineers to develop AI models and solutions tailored to business needs.

Your key responsibilities will include:
● Data Pipeline Development: Designing, building, and maintaining scalable data transformation, ingestion, and storage pipelines to support AI and machine learning applications.
● AI Model Deployment: Collaborating with data scientists and AI engineers to deploy machine learning and AI models into production environments.
● Infrastructure Automation: Automating AI infrastructure to streamline development workflows for data scientists and AI engineers.
● Model Development & Integration: Assisting in building AI models from the ground up, transforming machine learning models into APIs, and integrating them with other systems for real-world applications.
● Statistical Analysis: Conducting statistical analysis to interpret model results and inform business decisions.
● AI Experimentation: Running experiments and tests for machine learning models and AI applications, ensuring optimal performance.
● Collaboration: Partnering with cross-functional teams, including electronics and robotics departments, to integrate AI solutions effectively.
● System Maintenance: Monitoring and retraining systems to ensure continuous improvement and alignment with evolving business goals.
● Stakeholder Communication: Translating complex AI outcomes into actionable insights for business users and stakeholders.
● Other tasks required by CTO/ CEO.

Must have: 

● Educational Background:
○ Bachelor’s or Master’s degree in Computer Science, Data Engineering, Artificial Intelligence, or a related field.
● Technical Expertise:
○ Extensive experience in building data pipelines and deploying AI/ML models into production environments.
○ Proficiency in programming languages such as Python, Java, C++, or R.
○ Strong knowledge of statistics, calculus, and probability for algorithm development and model evaluation.
○ Hands-on experience with machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn.
● Cloud Experience:
○ Expertise in cloud services (e.g., AWS, Azure, or Google Cloud) with at least 3 years of experience in deploying AI models.
○ Must hold a relevant cloud certification, such as AWS Certified Data Analytics, AWS Certified Machine Learning Specialty, or equivalent.
● AI Specializations:
○ Familiarity with natural language processing, computer vision, and common AI model architectures.
○ Experience in transforming AI models into APIs for integration with other sytems.
● Additional Skills:
○ Solid understanding of data engineering practices, including ETL, feature engineering, and data preprocessing.
○ Ability to work collaboratively in an agile and fast-paced environment.
○ Strong problem-solving and communication skills.
○ Demonstrated ability to run AI experiments and optimize performance through testing.

 

● Preferred Qualifications:
○ Experience with robotics or electronics integration.
○ A track record of contributing to end-to-end AI product development.

● Work with the latest cloud technologies, and participate in diverse international projects;

● Dynamic work environment with helpful colleagues, working with people of many nationalities;

● Access to a complete set of learning platforms and continuous learning opportunities (certificates, boot camps, languages, etc.);

● Private medical insurance;

● Lunch voucher;

● Parking account;

● Well-being programs participation;

● Participate in the company’s training programs, AWS certification

● Participate in company events, company trip;