AI ENGINEER (SYNTHETIC IMAGERY) – Kingston Stanley – Dubai – UAE
Kingston Stanley invites applications for AI ENGINEER (SYNTHETIC IMAGERY) in Dubai, UAE
Job Title:
AI ENGINEER (SYNTHETIC IMAGERY), SECURITY ORGANIZATION – DUBAI, 6-MONTH CONTRACT
You must be an AI Engineer specializing in Synthetic Imagery, currently on a Freelance Visa in Dubai. You will be joining a growing Security company, heavily involved in AI and Big Data products that are sold to public and private sector clients.
This is a 6-month contract ONLY, with the possibility of extension at a later date.
Working hours for this role are:
- Monday to Thursday, 7:30am – 3:30pm
- Friday, 7am – 1pm
- Alternative Saturday’s, 7:30am – 12:30pm
- They work on a “one Saturday on, two Saturday’s off” model, so any candidate would only have to work two Saturday’s a month.
Responsibilities:
- End-to-End Machine Learning and Deep Learning Model Development:
- Lead the full lifecycle of machine learning projects, from initial data gathering and annotation to deploying models in production.
- Domain Knowledge in Synthetic Image Generation:
- Apply expertise in Synthetic Image Generation, preferably human faces.
- Technical Proficiency:
- Demonstrate advanced skills in Python programming, PyTorch, Huggingface, sklearn, pandas, Docker, and REST API development.
- Data Cleaning and Preprocessing:
- Perform EDA and data preprocessing and cleaning to prepare datasets for efficient and effective model training.
- Model Selection, Training, and Validation:
- Develop and train machine learning and deep learning models, employing SotA techniques and algorithms.
- Conduct thorough model selection processes, comparing and evaluating various models to determine the best fit for specific tasks.
- Testing, Benchmarking, and Scaling Models:
- Rigorously test models under various scenarios to ensure reliability and robustness.
- Benchmark model performance against industry standards and scale models to handle large-scale data efficiently.
- Deployment and MLOps:
- Deploy machine learning models into production environments, ensuring seamless integration and functionality.
- Employ MLOps practices for continuous integration, delivery, and model monitoring in production.
- Technical Documentation:
- Create comprehensive documentation for developed models and processes, detailing methodologies, codebases, and user guides.
- Ensure clear and understandable documentation for both technical and non-technical audiences, aiding in cross-departmental understanding and collaboration.
Qualifications:
- Bachelor’s or master’s degree in computer science, Artificial Intelligence, or Machine Learnig.
- 3+ years of industry experience with solid coding skills in Python, and experience with Docker, REST APIs, PyTorch, Transformers, sklearn, and other AI/ML frameworks/libraries.
- 1+ years of experience in Synthetic Image Generation systems.
- 3+ years of experience in end-to-end machine learning and deep learning model training on both CPU and GPU servers with parallelism experience
- Strong problem-solving skills with a focus on practical and scalable solutions.
- Excellent communication and collaboration abilities to work effectively in a team environment.
- Proactive in staying updated with the latest advancements in machine learning, deep learning, and related technologies.
- Experience with SQL, Elasticsearch, Cloud Services, and PySpark:
- Leverage SQL and Elasticsearch for data querying and manipulation.
- Utilize cloud services and PySpark for distributed computing and large-scale data processing.
- Incremental/Continual ML Model Training:
- Implement strategies for continual learning and model updating to adapt to new data and evolving requirements.
