Job Purpose:
A skilled and experienced Machine Learning Engineer to join our innovative team. The ideal candidate will have strong expertise in research and development (R&D), as well as the practical implementation of robust AI models.
The role requires a deep understanding of machine learning (ML), deep learning (DL), Generative AI models, including Large Language Models (LLMs), natural language processing (NLP), and speech analysis and recognition. The candidate should also have strong Python and Java programming skills, scripting experience, proficiency in ML frameworks and tools, microservices, Docker containers, automated ML pipelines, and basic DevOps practices.
Job Responsibilities:
- R&D Experimentation: Conduct cutting-edge research on ML, DL, Generative AI models, NLP, and speech recognition technologies to drive innovation and improve our AI solutions.
- Model Development: crawl data from various datasources, develop pipelines, build models, train, and optimize robust AI models using state-of-the-art techniques in NLP, speech analysis, and recognition.
- AI Service Packaging: Package AI models as services, ensuring they are ready for deployment in production environments.
- Deployment: Deploy AI services using microservices architecture and Docker containers for scalable and reliable operation.
- Automated Pipelines: Design and implement automated machine learning pipelines for model training, testing, and inference.
- Scalable Deployments: Develop and manage scalable deployments and distributed training processes to handle large-scale data and models.
- Performance Monitoring: Continuously monitor and evaluate model performance, making necessary adjustments to improve accuracy and efficiency.
- Collaboration: Work closely with cross-functional teams, including data scientists, product managers, and software engineers, to deliver high-quality AI solutions.
Technical Skills:
- Deep understanding of ML, DL, Generative AI models, NLP, and speech analysis and recognition.
- Proficiency in Python and Java programming and strong coding skills.
- Experience with microservices architecture and Docker containers.
- Expertise in automated ML pipelines for training, testing, and inference.
- Knowledge of scalable deployments and distributed training techniques.
- Familiarity with Ubuntu server commands and basic DevOps skills.
Preferred Educational Qualifications and Professional Certifications
- Bachelor's degree in Artificial Intelligence, Computer Science, or a relevant field.
Experience
- UAE National fresh graduates are encouraged to apply.
- 1–2 years of experience in AI/ML is required.
- Proven experience in machine learning engineering, with a focus on R&D and production-level deployment.
- Extensive hands-on experience with ML frameworks and tools such as TensorFlow, PyTorch, etc.
