Senior Machine Learning Engineer

Saal.ai; Abu Dhabi Emirate; On-site; AED 300,000 - 420,000; Full time

Job summary

Saal.ai in Abu Dhabi is seeking a Senior Machine Learning Engineer to lead the design, training, and deployment of AI models including NLP, DL, and LLM-based systems. You will guide junior engineers and collaborate with product teams to deliver scalable AI solutions.

The role requires strong full-stack and software development skills, expertise with Docker and microservices, and experience deploying models to production with automated pipelines and monitoring.

Qualifications

• 5+ years of AI/ML experience with a focus on building and deploying AI models.
• Hands-on experience with transformers and LLMs, fine-tuning and deployment.

Responsibilities

• Lead junior to mid-level ML engineers and developers.
• Build, train, and optimize AI models for NLP, speech, and recognition.
• Package AI models as services for production deployment.
• Deploy AI services using microservices and Docker containers.
• Design and implement automated ML pipelines for training, testing and inference.
• Oversee scalable deployments and distributed training processes.
• Monitor model performance and iterate for improvements.
• Contribute to full-stack development and software engineering practices.
• Collaborate with data scientists, product managers, and software engineers.

Skills

ML engineering

Deep learning

NLP

LLMs

Python

Java

Full-stack development

Docker

Education

Master's degree in Artificial Intelligence or CS

Tools

TensorFlow

PyTorch

Docker

Microservices

Job description

Saal.ai is seeking a highly skilled and experienced Senior Machine Learning Engineer to join our innovative team. The ideal candidate will have a strong background in machine learning (ML), deep learning (DL), Generative AI models including Large Language Models (LLMs), natural language processing (NLP), speech analysis and recognition, as well as agentic frameworks and relevant tools. This role requires leading junior to mid-level ML engineers and developers, driving the development of robust AI models, and ensuring their deployment in production environments. The candidate must also possess strong full-stack and software development skills.

Key Responsibilities:

• Team Leadership: Mentor and guide junior to mid-level ML engineers and developers, fostering a collaborative and innovative environment.
• Model Development: Build, 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.
• Full-Stack Development: Utilize strong full-stack development skills to contribute to the software development lifecycle, including front-end and back-end development.
• Software Engineering: Apply software engineering best practices in the development, testing, and maintenance of AI systems.
• 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, with strong coding skills and experience in developing large-scale AI systems.
• Experience with microservices architecture and Docker containers for developing and deploying scalable AI services.
• Expertise in designing and implementing automated ML pipelines for efficient model training, testing, and inference.
• Knowledge of scalable deployments and distributed training techniques, leveraging cloud platforms and distributed computing resources.
• Strong full-stack development skills, including proficiency in front-end and back-end technologies.
• Familiarity with Ubuntu server commands and basic DevOps skills, ensuring robust and reliable AI infrastructure.
• Experience working with NLP AI models processing Arabic language models.

LLM and Agentic Skills:

• In-depth understanding of Large Language Models (LLMs) and their architectures, including transformer-based models like GPT (Generative Pre-trained Transformer) and BERT (Bidirectional Encoder Representations from Transformers).
• Experience in fine-tuning and training large language models on specific tasks or domains, such as text generation, language translation, or sentiment analysis.
• Proficiency in working with pre-trained LLMs and adapting them to custom applications, including handling tasks like tokenization, attention mechanisms, and context understanding.
• Knowledge of techniques for optimizing LLMs for performance, including parameter tuning, regularization, and model compression.

Experience:

• 5+ Years Experience required in AI/ML
• Proven experience in machine learning engineering with a focus on building and deploying AI models.
• Extensive hands-on experience with ML frameworks and tools (TensorFlow, PyTorch, etc.).
• Hands-on experience with transformers AI models, language models, and fine-tuning/training large language models (LLMs).

Preferred Educational Qualifications and Professional Certifications:

Master's degree in Artificial Intelligence, Computer Science, or a relevant field.

Proficiency in Arabic language is a must