Senior Consultant - AI Engineer Job
Elm Company
Date: 3 hours ago
City: Riyadh
Contract type: Full time
ROLE PURPOSE
The aim is to state the overall significance of the job from the organization’s perspective.
is responsible for leading the development and deployment of GenAI solutions from prototype to production. This role focuses on building scalable systems, fine-tuning large language and multimodal models, and ensuring enterprise.
Key Accountabilities & Activities
This section describes the principal outputs required from the job.
Key Accountabilities
Key Activities
1-
AI Engineering and Delivery
Model Development & Optimization
Integration & Infrastructure
Evaluation & Monitoring
Policies, Processes & Procedures
6-
Information Security
The aim is to state the overall significance of the job from the organization’s perspective.
is responsible for leading the development and deployment of GenAI solutions from prototype to production. This role focuses on building scalable systems, fine-tuning large language and multimodal models, and ensuring enterprise.
Key Accountabilities & Activities
This section describes the principal outputs required from the job.
Key Accountabilities
Key Activities
1-
AI Engineering and Delivery
- Lead the full engineering lifecycle for Generative AI models, from prototyping to production deployment.
- Architect scalable and observable systems for model inference, including autoscaling, logging, tracing, and performance monitoring.
- Ensure stable delivery of production-ready models.
Model Development & Optimization
- Fine-tune LLMs and multimodal models using curated datasets for task- specific accuracy and alignment.
- Build modular pipelines for training, evaluation, and deployment using tools like Airflow, Ray, etc.
- Implement RAG systems using FAISS, Pinecone, or similar.
Integration & Infrastructure
- Translate research models into scalable APIs and services.
- Optimize infrastructure for inference (cloud/hybrid), balancing latency, cost, and throughput.
- Integrate GenAI apps into MLOps platforms with proper versioning, CI/CD, and governance.
Evaluation & Monitoring
- Develop evaluation frameworks using offline (e.g., BLEU, ROUGE, perplexity) and online (e.g., A/B testing, user feedback) signals.
- Lead model testing and validation to ensure safety, accuracy, and compliance with regulations and ethical guidelines.
Policies, Processes & Procedures
- Contribute to the development and implementation of relevant policies, procedures, and controls within the unit to ensure efficient and compliant delivery of AI engineering activities.
- Ensure adherence to internal standards and continuously seek improvement opportunities in delivery processes to enhance quality and reduce operational
6-
Information Security
- Ensure that all activities comply with the company’s information security
- Maintain confidentiality, integrity, and availability of information assets in alignment with organizational and regulatory requirements.
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