استخدام End-to-End Machine Learning Engineer (Generalist-Remote)

- Please include your WhatsApp number in your resume so we can contact you via WhatsApp.

- This job is fully remote with flexible hours, but you will need a good and stable internet connection for model training/deployment and team collaboration.

 We will send you a Google form and ask you to fill out all the fields in English. 

If your application meets our criteria, we’ll invite you for an online technical interview (may include a small ML task).

To apply, please send your resume, any relevant project links (GitHub, Kaggle, personal portfolio), and a brief introduction.

We are IdealTech, a digital agency that builds AI-powered solutions for our clients. We develop text-based chatbots, image recognition, voice cloning, video generation, etc.

We are looking for an Full-Stack Machine Learning Engineer (Generalist) for remote collaboration. If you meet the specialized conditions of this advertisement, we would be happy to have you as a member of our AI team.

We’re seeking a generalist Machine Learning Engineer who can handle tasks end-to-end: from choosing the right pretrained models on HuggingFace (or other open-source websites) to fine-tuning and deploying them for production use. 

You should be comfortable switching between multiple data modalities (text, images, audio, etc.) and have solid software engineering skills to integrate these models into real-world applications using APIs on on-device AI chips.

 

1-    Model Selection & Fine-Tuning

                  ·      Identify, download, and evaluate open-source models (e.g., from HuggingFace).

                  ·      Fine-tune or adapt these models for specific needs (NLP tasks, computer vision tasks, etc.).

2-    Full Pipeline Ownership

                  ·      Set up training pipelines (data preprocessing, model training, validation, hyperparameter tuning).

                  ·      Manage your own MLOps to deploy models into production environments.

3-    Data Handling & Integration

                  ·      Work with diverse datasets, use best practices in data cleaning and efficient I/O.

                  ·      Integrate ML solutions into client applications (APIs, batch pipelines, CRON jobs)

4-    Cross-Functional Collaboration

                  ·      Communicate effectively with project managers, designers, and other developers.

                  ·      Participate in requirement gathering and solution design for various AI/ML projects.

 

         ·        Solid ML Foundation: Machine learning fundamentals (regression, classification, overfitting, bias-variance tradeoff, etc.) and experience with at least one major deep learning framework (e.g., PyTorch or TensorFlow).

         ·        HuggingFace / Open-Source Models: Hands-on experience downloading, fine-tuning, and customizing existing models.

         ·        Software Engineering Skills: Experience writing clean, production-grade code in Python; familiarity with Git, testing frameworks, and CI/CD pipelines.

         ·        Data Pipeline & MLOps: Comfortable setting up training pipelines, handling large datasets, and deploying models

         ·        Experience with different Modalities:

-        Natural Language Processing (e.g., text classification, summarization)

-        Computer Vision (e.g., object detection, image classification)

-        Audio/Speech (e.g., speech-to-text, audio classification)

-        Time-Series/Structured Data (e.g. data logs)

         ·        Problem-Solving & Adaptability: Ability to quickly research and adopt new libraries or frameworks to solve unique client challenges.