Computer Vision & Machine Learning Engineer
Computer Vision & Machine Learning Engineer
Location:Â Worldwide (Remote)
Duration:Â 6 months (with possible extension)
Hours:Â Flexible (see below)
Rate:Â Competitive (see below)
Introduction
The Syria Justice and Accountability Centre (SJAC) is Computer Vision & Machine Learning Engineer (Consultant) for a 6-month remote engagement, with potential extension. The role supports mission-driven projects using open-source tools, emphasizing scalability and reliability.
The ideal candidate will bring deep expertise in visual computing and natural language processing (preferably Multilingual NLP and RTL languages such as Arabic), with a strong track record of applying these skills to real-world problems. You should be comfortable working across the full ML lifecycle, from model design and training to deployment and monitoring, and be motivated by work that combines technical innovation with social impact.
Scope of Work
Design and optimize computer vision and machine learning algorithms.
Build scalable CV systems for large image datasets.
Develop preprocessing pipelines (e.g., detection, deskewing) to enhance OCR.
Evaluate OCR technologies/models optimized for Arabic documents.
Build end-to-end pipelines from image input to feature extraction, classification, and clustering.
Solve technical challenges in CV and integrate models into SJAC products.
Write clean, production-grade code following best practices.
Required Qualifications
Education & Core Expertise
MSc in Computer Vision or Machine Learning, or BSc in Computer Science with AI or CV specialization. Equivalent relevant working experience may be accepted.
Proven experience in the fields of Computer Vision and Machine Learning (specifically Deep Learning).
Track record of leading CV/ML projects from concept to production.
Technical Skills
Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
Experience with both ML-based and traditional CV techniques, including OpenCV.
Strong understanding of modern deep learning architectures, including transformer-based.
Hands-on experience with open-source libraries and model hubs, such as Hugging Face.
Deployment & Infrastructure
Experience deploying ML models on cloud platforms (e.g., AWS) with resource constraints.
Skilled in designing production ML pipelines using MLOps tools (versioning, workflows, monitoring, optimization)
Ability to evaluate and optimize ML systems for metrics such as speed, scalability, and power consumption.
Bonus Skills
Ability to read and understand Arabic is a strong plus.
Familiarity with ML-based OCR technologies.
Hands-on experience with open-source libraries and model hubs, such as Hugging Face.
Familiarity with large vision models and multimodal architectures.
The contract may be extended beyond the initial six-month period based on performance and funding availability. Candidates are asked to propose an hourly rate for their services. The final rate and working hours will be agreed with the successful candidate.