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Senior Machine Learning Engineer
15 minutes ago
We are seeking a highly skilled Senior Machine Learning Engineer to design, deploy, and optimize AI applications at scale. This role combines expertise in ML model development with modern deployment practices, ensuring robust, scalable solutions in production environments.
Inception is the UAE's national-scale enabler in AI Research and Development. Partnering with Microsoft's AI SaaS, we offer domain-specific Agentic AI Orchestrator platforms utilizing reasoning agents for precise and cost-effective services. Our focus includes AI incubation, IP creation, applied AI R&D, and AI investment products. By creating models tailored to specific domains and languages, we ensure superior accuracy and efficiency. Collaborating with top universities and industry giants to drive significant advancements in AI technology within the region.
Key Responsibilities
- Design and implement ML models and pipelines for large-scale AI applications.
- Build and manage CI/CD pipelines for ML workflows.
- Deploy and maintain AI services using Azure Kubernetes Service (AKS) and Kubernetes.
- Integrate Agentic Pipelines for advanced AI orchestration.
- Optimize latency and scalability for LLM-based applications.
- Collaborate with cross-functional teams to ensure seamless deployment in production environments.
- Drive LLMOps best practices for managing large language models in cloud environments.
- Work on AI Search integration and modern deployment techniques.
- Ensure compliance and performance across Microsoft Azure Stack, with flexibility for GCP and AWS.
Required Skills & Experience
- Strong experience in CI/CD and DevOps for ML systems.
- Hands-on with frameworks like VLLM and Slang for serving LLMs.
- Proficiency in Azure Pipelines, AKS, and container orchestration.
- Knowledge of LLMOps, latency optimization, and scalability strategies.
- Experience deploying AI applications in cloud environments at scale.
- Familiarity with Agentic Pipelines and modern ML deployment techniques.
- Preference for Microsoft Azure, but exposure to GCP/AWS is a plus.
- Solid understanding of production-grade ML systems and monitoring.
- Strong sense of ownership and the ability to drive tasks to completion
Qualifications
- Bachelor's or master's in computer science, AI/ML, or related field.
- 5+ years of experience in ML engineering and cloud deployment.
- Strong programming skills in Python and ML frameworks.
- Excellent problem-solving and collaboration skills.
