AI Engineer - Machine Learning Systems
Posted date [2026-07-23]
(ID: 48551)
 |
YO IT Consulting specializes in recruiting remote professionals for AI training and data annotation projects with global companies. Based in Abu Dhabi Emirate, United Arab Emirates, the company connects qualified talent worldwide with flexible remote opportunities that contribute to the development and improvement of modern artificial intelligence systems. |
Job Description and Requirements
AI Engineer - Machine Learning SystemsJob Snapshot
Role: AI Engineer - Machine Learning Systems
Location: Abu Dhabi Emirate, United Arab Emirates
Industry: IT and Services
Function: Software Engineering / Web Development
Experience: Proven experience developing and deploying production machine learning systems
Job Type: Contract - Remote
Position Overview
AI Engineer - Machine Learning Systems in Abu Dhabi Emirate, United Arab Emirates is a fully remote IT and Services opportunity with YO IT Consulting for qualified professionals based anywhere in the world. The company is hiring an AI Engineer to design production-grade machine learning models, automate deployment pipelines, and contribute expert technical input used to improve next-generation artificial intelligence systems.
The successful candidate will combine machine learning engineering, cloud infrastructure, software development, and container orchestration expertise. The role involves translating complex real-world data challenges into scalable AI solutions using Python
or Java, AWS, Kubernetes, and modern continuous integration and continuous delivery practices.
Job Details
Country: United Arab Emirates
City: Abu Dhabi Emirate
Industry: IT and Services
Function: Software Engineering / Development
Salary: 18000-30000
Estimated salary range based on similar jobs in the job city; please confirm the final offer with the employer.
Gender: Any
Candidate Nationality: Any
Candidate Preferred Location: Any
Job Type: Contract - Remote - work from home
Role Context
The AI Engineer will work remotely on technical projects that help train, evaluate, and improve advanced artificial intelligence systems. Although previous experience in AI training is not required, candidates must possess strong professional knowledge of machine learning engineering, software development, model deployment, and cloud-based infrastructure.
The role will focus on designing robust machine learning solutions, preparing real-world data problems for model development, and creating reliable production workflows. The engineer will collaborate with data scientists, researchers, and software professionals while documenting technical decisions with accuracy and clarity.
Key Responsibilities
* Design, develop, test, and optimize machine learning models for production environments.
* Translate complex business and data challenges into practical machine learning solutions.
* Evaluate real-world data problems and determine suitable modeling approaches.
* Frame machine learning objectives, assumptions, constraints, and success criteria.
* Prepare, clean, transform, and validate datasets for model development and evaluation.
* Select suitable machine learning algorithms based on business requirements and data characteristics.
* Train models and evaluate their accuracy, reliability, scalability, and operational suitability.
* Improve model performance through feature engineering, parameter tuning, validation, and error analysis.
* Build production-ready machine learning services that integrate with existing software systems.
* Develop automated end-to-end machine learning pipelines.
* Implement continuous integration and continuous delivery workflows for model testing and deployment.
* Automate model validation, packaging, release, monitoring, and rollback processes.
* Apply software engineering standards to machine learning codebases and supporting services.
* Develop maintainable applications using Python, Java, or other suitable programming languages.
* Work with large-scale software systems and distributed technical environments.
* Use AWS cloud services to build scalable machine learning infrastructure.
* Deploy models, applications, data pipelines, and supporting services within AWS environments.
* Configure cloud resources for performance, availability, security, and cost efficiency.
* Orchestrate containerized machine learning workloads using Kubernetes.
* Configure scalable deployments, services, jobs, resource controls, and availability mechanisms.
* Support reliable model execution across development, testing, and production environments.
* Monitor production machine learning services and investigate performance or reliability problems.
* Collaborate with data scientists to convert experimental models into dependable production solutions.
* Work with engineers and researchers to evaluate technical approaches and implementation trade-offs.
* Participate in technical reviews and provide practical recommendations based on engineering evidence.
* Identify opportunities to simplify machine learning workflows and improve deployment speed.
* Develop reusable tools, components, templates, and automation mechanisms.
* Document model architecture, infrastructure design, deployment processes, and technical decisions.
* Explain complex technical findings clearly to both specialist and non-specialist stakeholders.
* Maintain accurate records of experiments, assumptions, implementation choices, and evaluation results.
* Review generated AI outputs and provide high-quality technical feedback where required.
* Contribute domain expertise that helps advanced AI systems learn, reason, and perform more effectively.
* Complete assigned technical tasks independently while meeting quality and delivery requirements.
Ideal Profile
* Proven expertise in machine learning algorithms, model development, and production deployment.
* Strong understanding of supervised, unsupervised, and other relevant machine learning techniques.
* Professional programming skills in Python or Java.
* Experience contributing to large-scale software engineering projects.
* Strong knowledge of software architecture, testing, version control, and maintainable code development.
* In-depth experience implementing continuous integration and continuous delivery workflows.
* Familiarity with automated testing, deployment, monitoring, and release-management tools.
* Hands-on experience using AWS services for machine learning applications and data pipelines.
* Advanced knowledge of Kubernetes and containerized workload orchestration.
* Experience using Docker or comparable container technologies.
* Ability to scope, structure, and solve complex real-world data problems.
* Strong understanding of data preprocessing, feature engineering, model evaluation, and performance optimization.
* Ability to work independently within a fully remote professional environment.
* Excellent written and verbal communication skills.
* Strong technical documentation and cross-functional collaboration capabilities.
* Ability to explain solution approaches, risks, assumptions, and trade-offs clearly.
* Familiarity with TensorFlow, PyTorch, or comparable deep learning frameworks is preferred.
* Previous experience working in a startup or high-growth technology environment is advantageous.
* A strong publication record or contributions to open-source artificial intelligence projects are beneficial.
* Previous AI training experience is not required.
Skills Set
* Artificial intelligence
* Machine learning
* Machine learning engineering
* Model development
* Model deployment
* Production machine learning
* Python
* Java
* Software engineering
* Machine learning pipelines
* Continuous integration
* Continuous delivery
* CI-CD automation
* AWS
* Cloud infrastructure
* Kubernetes
* Docker
* Container orchestration
* Model evaluation
* Data preprocessing
* Feature engineering
* Hyperparameter tuning
* Data pipelines
* Distributed systems
* TensorFlow
* PyTorch
* Deep learning
* Model monitoring
* Technical documentation
* Cross-functional collaboration
* Problem-solving
* Open-source development
* Remote work
Why Join Us
This fully remote contract opportunity enables experienced machine learning professionals to contribute to projects that support the development of advanced artificial intelligence systems. Candidates may work from any country while being associated with a UAE-based role in Abu Dhabi Emirate.
The position offers technically challenging work involving production machine learning, AWS infrastructure, Kubernetes orchestration, software engineering, and AI evaluation. It is well suited to an independent engineer seeking flexible remote work and the opportunity to apply practical expertise to emerging AI systems.
About the Company
YO IT Consulting specializes in recruiting remote professionals for AI training and data annotation projects with global companies. Based in Abu Dhabi Emirate, United Arab Emirates, the company connects qualified talent worldwide with flexible remote opportunities that contribute to the development and improvement of modern artificial intelligence systems.
Job Details
Country: United Arab Emirates
City: Abu Dhabi Emirate
Industry: IT and Services
Function: Software Engineering / Development
Salary: 18000-30000
Estimated salary range based on similar jobs in the job city; please confirm the final offer with the employer.
Gender: Any
Candidate Nationality: Any
Candidate Preferred Location: Any
Job Type: Contract - Remote - work from home
Role Context
The AI Engineer will work remotely on technical projects that help train, evaluate, and improve advanced artificial intelligence systems. Although previous experience in AI training is not required, candidates must possess strong professional knowledge of machine learning engineering, software development, model deployment, and cloud-based infrastructure.
The role will focus on designing robust machine learning solutions, preparing real-world data problems for model development, and creating reliable production workflows. The engineer will collaborate with data scientists, researchers, and software professionals while documenting technical decisions with accuracy and clarity.
Key Responsibilities
* Design, develop, test, and optimize machine learning models for production environments.
* Translate complex business and data challenges into practical machine learning solutions.
* Evaluate real-world data problems and determine suitable modeling approaches.
* Frame machine learning objectives, assumptions, constraints, and success criteria.
* Prepare, clean, transform, and validate datasets for model development and evaluation.
* Select suitable machine learning algorithms based on business requirements and data characteristics.
* Train models and evaluate their accuracy, reliability, scalability, and operational suitability.
* Improve model performance through feature engineering, parameter tuning, validation, and error analysis.
* Build production-ready machine learning services that integrate with existing software systems.
* Develop automated end-to-end machine learning pipelines.
* Implement continuous integration and continuous delivery workflows for model testing and deployment.
* Automate model validation, packaging, release, monitoring, and rollback processes.
* Apply software engineering standards to machine learning codebases and supporting services.
* Develop maintainable applications using Python, Java, or other suitable programming languages.
* Work with large-scale software systems and distributed technical environments.
* Use AWS cloud services to build scalable machine learning infrastructure.
* Deploy models, applications, data pipelines, and supporting services within AWS environments.
* Configure cloud resources for performance, availability, security, and cost efficiency.
* Orchestrate containerized machine learning workloads using Kubernetes.
* Configure scalable deployments, services, jobs, resource controls, and availability mechanisms.
* Support reliable model execution across development, testing, and production environments.
* Monitor production machine learning services and investigate performance or reliability problems.
* Collaborate with data scientists to convert experimental models into dependable production solutions.
* Work with engineers and researchers to evaluate technical approaches and implementation trade-offs.
* Participate in technical reviews and provide practical recommendations based on engineering evidence.
* Identify opportunities to simplify machine learning workflows and improve deployment speed.
* Develop reusable tools, components, templates, and automation mechanisms.
* Document model architecture, infrastructure design, deployment processes, and technical decisions.
* Explain complex technical findings clearly to both specialist and non-specialist stakeholders.
* Maintain accurate records of experiments, assumptions, implementation choices, and evaluation results.
* Review generated AI outputs and provide high-quality technical feedback where required.
* Contribute domain expertise that helps advanced AI systems learn, reason, and perform more effectively.
* Complete assigned technical tasks independently while meeting quality and delivery requirements.
Ideal Profile
* Proven expertise in machine learning algorithms, model development, and production deployment.
* Strong understanding of supervised, unsupervised, and other relevant machine learning techniques.
* Professional programming skills in Python or Java.
* Experience contributing to large-scale software engineering projects.
* Strong knowledge of software architecture, testing, version control, and maintainable code development.
* In-depth experience implementing continuous integration and continuous delivery workflows.
* Familiarity with automated testing, deployment, monitoring, and release-management tools.
* Hands-on experience using AWS services for machine learning applications and data pipelines.
* Advanced knowledge of Kubernetes and containerized workload orchestration.
* Experience using Docker or comparable container technologies.
* Ability to scope, structure, and solve complex real-world data problems.
* Strong understanding of data preprocessing, feature engineering, model evaluation, and performance optimization.
* Ability to work independently within a fully remote professional environment.
* Excellent written and verbal communication skills.
* Strong technical documentation and cross-functional collaboration capabilities.
* Ability to explain solution approaches, risks, assumptions, and trade-offs clearly.
* Familiarity with TensorFlow, PyTorch, or comparable deep learning frameworks is preferred.
* Previous experience working in a startup or high-growth technology environment is advantageous.
* A strong publication record or contributions to open-source artificial intelligence projects are beneficial.
* Previous AI training experience is not required.
Skills Set
* Artificial intelligence
* Machine learning
* Machine learning engineering
* Model development
* Model deployment
* Production machine learning
* Python
* Java
* Software engineering
* Machine learning pipelines
* Continuous integration
* Continuous delivery
* CI-CD automation
* AWS
* Cloud infrastructure
* Kubernetes
* Docker
* Container orchestration
* Model evaluation
* Data preprocessing
* Feature engineering
* Hyperparameter tuning
* Data pipelines
* Distributed systems
* TensorFlow
* PyTorch
* Deep learning
* Model monitoring
* Technical documentation
* Cross-functional collaboration
* Problem-solving
* Open-source development
* Remote work
Why Join Us
This fully remote contract opportunity enables experienced machine learning professionals to contribute to projects that support the development of advanced artificial intelligence systems. Candidates may work from any country while being associated with a UAE-based role in Abu Dhabi Emirate.
The position offers technically challenging work involving production machine learning, AWS infrastructure, Kubernetes orchestration, software engineering, and AI evaluation. It is well suited to an independent engineer seeking flexible remote work and the opportunity to apply practical expertise to emerging AI systems.
About the Company
YO IT Consulting specializes in recruiting remote professionals for AI training and data annotation projects with global companies. Based in Abu Dhabi Emirate, United Arab Emirates, the company connects qualified talent worldwide with flexible remote opportunities that contribute to the development and improvement of modern artificial intelligence systems.
