Robusta Studio

Senior AI Developer

Robusta Studio

full-time

Posted on:

Location Type: Remote

Location: Egypt

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Job Level

Senior

Tech Stack

ApacheCloudDockerETLFlaskGoogle Cloud PlatformGraphQLHadoopJenkinsKafkaKerasKubernetesMongoDBNoSQLNumpyPandasPostgresPythonPyTorchScikit-LearnSparkSQLTensorflow

About the role

  • 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

  • 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
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
Pythonmachine learningdeep learningTensorFlowKerasPyTorchScikit-learndata preprocessingdata analysisRESTful API
Soft Skills
collaborationcommunicationcontinuous improvementdocumentationreporting