Senior Machine Learning Engineer

Key Responsibilities :: Arabic Speaker is a must

• 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.

Required Skills and Qualifications

• Education: Master's degree in Artificial Intelligence, Computer Science, or a relevant

field. A Ph.D. is a plus.

Experience:

o Proven experience in machine learning engineering with a focus on building and

deploying AI models.

o Extensive hands-on experience with ML frameworks and tools (TensorFlow,

PyTorch, etc.).

o Hands-on experience with transformers AI models, language models, and finetuning/

training large language models (LLMs).

Technical Skills:

o Deep understanding of ML, DL, Generative AI models, NLP, and speech analysis

and recognition.

o Proficiency in Python and Java programming, with strong coding skills and

experience in developing large-scale AI systems.

o Experience with microservices architecture and Docker containers for developing

and deploying scalable AI services.

o Expertise in designing and implementing automated ML pipelines for efficient

model training, testing, and inference.

o Knowledge of scalable deployments and distributed training techniques,

leveraging cloud platforms and distributed computing resources.

o Strong full-stack development skills, including proficiency in front-end and backend

technologies.

o Familiarity with Ubuntu server commands and basic DevOps skills, ensuring

robust and reliable AI infrastructure.

o Experience working with NLP AI models processing Arabic language models.

LLM Skills:

o In-depth understanding of Large Language Models (LLMs) and their

architectures, including transformer-based models like GPT (Generative Pretrained

Transformer) and BERT (Bidirectional Encoder Representations from

Transformers).

o Experience in fine-tuning and training large language models on specific tasks or

domains, such as text generation, language translation, or sentiment analysis.

o Proficiency in working with pre-trained LLMs and adapting them to custom

applications, including handling tasks like tokenization, attention mechanisms,

and context understanding.

o Knowledge of techniques for optimizing LLMs for performance, including

parameter tuning, regularization, and model compression.