AI Engineer – Computer Vision, Applied GenAI

Job not on LinkedIn

🔥 1 minute ago

🇯🇴 Jordan – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

👁️ Computer Vision Engineer

👻 Ghost score 15%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Arabian Agile Professionals

WebsiteLinkedInAll Job Openings

1 - 10 employees

Founded 2024

🏥 Healthcare

📚 Education

💼 Consulting

Healthcare • Education • Consulting

Arabian Agile Professionals is a consulting firm led by Suhaib Ajlouni, a tech innovator and leader passionate about leveraging technology for smarter and safer solutions in the digital realm. With extensive experience in agile project management, technical team leadership, and entrepreneurial guidance, the firm focuses on helping organizations optimize agile practices, develop technical leadership skills, and support startups in navigating their challenges. Suhaib's commitment to innovation, adaptability, and community building integrates technology with human well-being, emphasizing excellence and continuous learning.

📋 Description

• Design, train, fine-tune, and evaluate models for detection, classification, segmentation, and tracking • Integrate computer vision models into production pipelines • Build LLM-powered features including RAG, tool-using agents, and structured extraction • Build prompt and evaluation infrastructure • Write APIs, data pipelines, batch jobs, streaming jobs, and storage services around models • Optimize models for target hardware through quantization, batching, and edge-device inference • Define and track quality metrics and establish measurable baselines • Instrument, monitor, and debug production models for drift, latency, and failure modes • Work with product and business stakeholders to create scoped, measurable deliverables • Document systems and features for future engineers • Own AI work end to end from model and data through production service and validation evidence

🎯 Requirements

• 3 to 5 years building and shipping machine learning or AI systems in production • Strong Python • Clean, tested, reviewable code; not notebook-only output • Practical depth in computer vision or applied generative AI, with working familiarity in the other area • Computer vision: PyTorch or TensorFlow, OpenCV, modern detection and segmentation architectures, dataset creation and annotation workflows • Applied GenAI: LLM APIs and open-weight models, RAG, embeddings and vector stores, agent frameworks, prompt design, and systematic evaluation • Solid software engineering fundamentals: Git, code review, testing, CI, Docker, and Linux command line • Experience deploying a model as a service and maintaining it in operation • Cloud deployment experience with AWS, Azure, or GCP • Basic observability • SQL and general data handling • Fluent written and spoken English • Self-direction required for remote work • German is a strong plus; B1 or higher is advantageous but not required • Edge and embedded inference experience with NVIDIA Jetson, TensorRT, ONNX Runtime, or OpenVINO • Video streaming and industrial camera experience with RTSP, GStreamer, GenICam, or machine vision cameras • MLOps tooling experience with MLflow, Weights and Biases, DVC, Kubernetes, or model registries • Experience in an industrial, robotics, IoT, or B2B product environment • Public track record through open source contributions, technical writing, or published work

🏖️ Benefits

• Competitive salary, benchmarked to the Amman market for this level • Fully remote setup • Real ownership of features that reach customers • Direct exposure to the European market and to senior technical decision making • Asynchronous written communication as the default • Reasonable overlap window with the European working day • Small teams, short decision paths, and direct access to the people who set priorities • Human oversight, data protection and security integrated into the definition of done