IT Services and IT Consulting👥 201 employees📍 Dubai, Dubai, AEEst. 2014
A dynamic solution provider, passionate about building smart, modular, comprehensive, and sustainable solutions for today’s world of business.
We resolve problems, improve operations and enhance cu…
Job Overview
We are seeking a Senior Machine Learning Engineer to join our team in a Hybrid work arrangement. This is a Full-time position located in Nasr City, Al Manteqah Al Oula, Egypt. The ideal candidate will lead the entire ML lifecycle from data collection and analysis to model deployment, monitoring, and optimization.
Key Responsibilities
Lead the entire ML lifecycle from data collection and analysis to model deployment, monitoring, and optimization.
Apply deep learning and NLP techniques to develop solutions, potentially enhancing systems like search or recommendation engines.
Design and implement end-to-end ML pipelines, incorporating MLOps best practices for CI/CD, containerization (Docker, Kubernetes), and cloud deployment (AWS, GCP, Azure).
Utilize LLM knowledge, including prompt engineering and fine-tuning, to build advanced generative AI applications and conversational AI solutions.
Perform comprehensive data analytics, including statistical analysis and feature engineering, to inform model development and extract actionable insights from large datasets.
Write production-quality, robust code in Python (and potentially other languages like Java or Scala), ensuring code quality through reviews and testing.
Collaborate with cross-functional teams, including data scientists, data engineers, and product managers, to translate business requirements into technical ML solutions.
Required Qualifications
We are looking for candidates with the following Required Skills and Qualifications:
Proven experience as a Machine Learning Engineer with a strong portfolio of deployed production models.
Proficiency in Python and relevant ML frameworks/libraries (e.g., TensorFlow, PyTorch, scikit-learn).
Expertise in data science methodologies, statistical analysis, and data analytics.
Hands-on experience with MLOps tools and practices for managing the ML application lifecycle.
Strong understanding of NLP and experience with LLMs and prompt engineering techniques.
Solid software engineering background with knowledge of data structures, algorithms, and system design.
Excellent problem-solving, communication, and collaboration skills.
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