Machine Learning Engineer
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Key skills for this role
About the Role
AppliedAI is seeking a Machine Learning Engineer to contribute to the development and optimization of Opus, the world's first Knowledge Work AI platform. The role involves building AI inference pipelines, optimizing model-serving performance, and implementing observability for AI components.
Key Skills for This Role
Responsibilities
- Develop and maintain AI inference and orchestration pipelines used in production
- Optimize model serving performance, latency, and reliability across live systems
- Implement observability, logging, and monitoring for AI components
- Contribute to prompt and alignment improvements to enhance response quality and consistency
- Refactor existing code for modularity, clarity, and maintainability
- Collaborate with senior engineers and product teams to deliver stable, user facing AI features
- Participate in design reviews, testing, and rollout of new systems and improvements
Requirements
- 2 4 years of experience in ML or backend engineering
- 1+ years working on LLM prompt design, model behavior shaping, or symbolic product logic integration into language systems
- Strong Python programming skills and understanding of production ML systems
- Familiar with orchestration tools (Airflow, Celery, Kubernetes) and cloud environments (AWS, GCP, Azure)
- Experience deploying and monitoring inference pipelines (e.g. LLMs, CV models, or similar APIs)
- Knowledge of observability tools and performance debugging
Full Job Posting
Role Overview
- As an Opus ML Engineer, you will contribute to the development, optimization, and reliability of Opus's AI infrastructure.
- You'll work in a cross functional UAE based team to build, maintain, and improve systems powering Opus's AI features.
- Focus on implementing clean, efficient, and observable systems for consistent AI performance.
Key Responsibilities
- Develop and maintain AI inference and orchestration pipelines used in production.
- Optimize model serving performance, latency, and reliability across live systems.
- Implement observability, logging, and monitoring for AI components.
- Contribute to prompt and alignment improvements to enhance response quality and consistency.
- Refactor existing code for modularity, clarity, and maintainability.
- Collaborate with senior engineers and product teams to deliver stable, user facing AI features.
- Participate in design reviews, testing, and rollout of new systems and improvements.
Qualifications
- 2 4 years of experience in ML or backend engineering.
- 1+ years working on LLM prompt design, model behavior shaping, or symbolic product logic integration into language systems.
- Strong Python programming skills and understanding of production ML systems.
- Familiar with orchestration tools (Airflow, Celery, Kubernetes) and cloud environments (AWS, GCP, Azure).
- Experience deploying and monitoring inference pipelines (e.g. LLMs, CV models, or similar APIs).
- Knowledge of observability tools and performance debugging.
Why Join AppliedAI
- Opportunity to work with a highly innovative AI technology company.
- Collaborative and innovative work environment.
- Growing, entrepreneurial and forward thinking culture.
- Career growth and professional development opportunities.
- Exposure to a thriving ecosystem working from our Abu Dhabi HQ.
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