AI Developer - Octopus by RTG
Cairo, Cairo Governorate, Egypt - Remote
robusta
Robusta Studio is RTG’s digital agency. We build customer engagement tools and apps focused on digital transformations that help businesses grow.Who we are;
Octopus by RTG is enabling a key partner organization to grow their tech teams while focusing on AI. We are currently looking for the right pioneers to join the team!
Octopus is proud to be part of the Robusta Technology Group (RTG), a leading tech group. With a decade of experience and a successful track record of delivering over 300 projects across Europe, the Middle East, and North America, RTG has established itself as a preferred employer in the Egyptian market. Octopus and Robusta are building a bridge between Europe and Africa, creating tailored hub solutions to connect companies with top talent across the globe.
Octopus is specialized in rapidly assembling remote & onsite global tech teams that are fully aligned with the culture and practices of a particular brand. By providing tailored hubs to suit its clients needs, Octopus gives companies all the advantages of remote work and offshoring without all the negatives.
You will be working with one of our partners in Saudi that is transforming the insurance industry in the Kingdom with smart, instant, and purposeful solutions
- Develop and Maintain AI Applications: Design and develop scalable AI-driven applications using Python.
- Model Training & Optimization: Build, train, and optimize machine learning models using tools like TensorFlow, Keras, PyTorch, and Scikit-learn.
- Gemini Integration: Apply deep knowledge of Gemini to integrate AI models and tools with Gemini’s features for improved functionality.
- Data Analysis & Preprocessing: Process and analyze large datasets to extract valuable insights and prepare them for machine learning.
- Algorithm Development: Design and implement machine learning algorithms tailored to specific business needs.
- Collaborate with Cross-Functional Teams: Work closely with data scientists, engineers, and other stakeholders to ensure AI solutions are aligned with business objectives.
- Continuous Improvement: Stay updated with the latest trends in AI, machine learning, and data science to ensure the use of the most advanced techniques.
- Documentation & Reporting: Document AI models, algorithms, and application workflows, and present findings to internal teams or clients.
Requirements
Required Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
- Experience: Minimum of 3 years of experience in AI application development using Python.
- Technical Skills:
- Programming Languages: Proficiency in Python with deep knowledge of libraries and frameworks commonly used in AI development.
- Machine Learning & Deep Learning:
- Extensive experience with machine learning algorithms (supervised, unsupervised, and reinforcement learning).
- Expertise in deep learning frameworks such as TensorFlow, Keras, PyTorch, and MXNet.
- Strong knowledge of natural language processing (NLP), computer vision (CV), and other specialized AI domains.
- Gemini:
- Hands-on experience with Gemini (or a similar platform) for integrating AI solutions into application development, including leveraging Gemini's features to optimize model performance, scalability, and deployment.
- Data Science & Data Processing:
- Proficient in data preprocessing, including cleaning, transformation, and feature engineering to prepare datasets for training.
- Advanced skills in data analysis and visualization with libraries like Pandas, NumPy, Matplotlib, and Seaborn.
- Familiarity with SQL and NoSQL databases for managing structured and unstructured data (e.g., PostgreSQL, MongoDB).
- Experience with big data processing frameworks like Apache Spark, Hadoop, and Dask.
- Cloud Platforms & Tools:
- Experience with cloud platforms ( GCP) and their AI/ML offerings like Google AI.
- Familiarity with containerization technologies such as Docker and orchestration tools like Kubernetes for deploying AI models at scale.
- Version Control:
- Expertise in using Git for source code management, including collaboration in a multi-developer environment.
- Model Deployment & Optimization:
- Hands-on experience deploying machine learning models to production environments, ensuring scalability, performance, and reliability.
- Familiarity with model serving technologies such as TensorFlow Serving, FastAPI, or Flask for creating APIs around models.
- Performance optimization skills for tuning model inference and training time using techniques like quantization, pruning, and distributed training.
- API Integration:
- Proficiency in RESTful API development for integrating machine learning models into production systems and web applications.
- Knowledge of GraphQL for more complex querying and API management.
- Security:
- Understanding of data privacy, encryption, and AI security practices to ensure the safe handling of sensitive data.
- Development Practices:
- Strong understanding of Agile methodologies for managing development cycles, particularly in machine learning and AI projects.
- Experience with CI/CD pipelines for automated testing, deployment, and model versioning (e.g., using Jenkins, GitLab CI, or CircleCI).
- Knowledge of Unit Testing and Test-Driven Development (TDD) to ensure model robustness and quality.
Preferred Qualifications
- Experience with Gemini: Advanced experience using Gemini for AI model development and deployment.
- Data Engineering: Experience in ETL (Extract, Transform, Load) pipelines, working with large datasets, and using frameworks like Apache Kafka or Apache Flink.
- Edge AI: Experience deploying AI models on edge devices for real-time processing, using frameworks like TensorFlow Lite or ONNX.
- Model Interpretability & Fairness: Familiarity with tools for explaining model predictions (e.g., SHAP, LIME) and ensuring AI models meet ethical and fairness standards.
Benefits
- Social and Medical Insurance
- Salary paid in USD
- Fully remote opportunity
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile API Development APIs Big Data CI/CD Computer Science Computer Vision Data analysis Deep Learning Docker Engineering ETL FastAPI Feature engineering Flask Flink GCP Gemini Git GitLab GraphQL Hadoop Jenkins Kafka Keras Kubernetes Machine Learning Matplotlib ML models Model deployment Model inference Model training MongoDB MXNet NLP NoSQL NumPy ONNX Pandas Pipelines PostgreSQL Privacy Python PyTorch Reinforcement Learning Scikit-learn Seaborn Security Spark SQL TDD TensorFlow Testing Unstructured data
Perks/benefits: Career development
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