AI Engineer (Synthetic Imagery), Security Organization \xe2\x80\x93 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 \xe2\x80\x93 3:30pm
• Friday, 7am \xe2\x80\x93 1pm
• Alternative Saturday\xe2\x80\x99s, 7:30am \xe2\x80\x93 12:30pm

• They work on a \xe2\x80\x9cone Saturday on, two Saturday\xe2\x80\x99s off\xe2\x80\x9d model, so any candidate would only have to work two Saturday\xe2\x80\x99s 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.

Kingston Stanley