AI Engineer – Computer Vision, Applied GenAI

This is a fully remote position, open to applicants in Jordan.

📋 Description

• Design, train, refine, and assess models for detection, classification, segmentation, and tracking.

• Integrate computer vision models into production workflows.

• Develop LLM-powered features such as RAG, tool-using agents, and structured extraction.

• Create infrastructure for prompt and evaluation.

• Develop APIs, data pipelines, batch jobs, streaming jobs, and storage services surrounding models.

• Optimize models for target hardware through quantization, batching, and inference on edge devices.

• Establish and monitor quality metrics, as well as define measurable baselines.

• Instrument, monitor, and troubleshoot production models for drift, latency, and failure modes.

• Collaborate with product and business stakeholders to produce scoped, measurable deliverables.

• Document systems and features for future engineers.

• Manage AI projects from model and data development through to production service and validation evidence.

⛳️ Requirements

• 3 to 5 years of experience in building and deploying machine learning or AI systems in production.

• Proficient in Python.

• Ability to write clean, tested, and reviewable code; not just notebook outputs.

• Practical expertise in computer vision or applied generative AI, with a working knowledge in the other domain.

• For computer vision: Experience with PyTorch or TensorFlow, OpenCV, modern detection and segmentation architectures, and dataset creation and annotation workflows.

• For applied GenAI: Familiarity with LLM APIs and open-weight models, RAG, embeddings and vector stores, agent frameworks, prompt design, and systematic evaluation.

• Strong software engineering fundamentals: Git, code review, testing, CI, Docker, and Linux command line.

• Experience in deploying a model as a service and maintaining its operation.

• Cloud deployment experience with AWS, Azure, or GCP.

• Basic observability skills.

• Proficient in SQL and general data handling.

• Fluent in written and spoken English.

• Self-direction is essential for remote work.

• Proficiency in German is a strong advantage; B1 level or higher is beneficial but not mandatory.

• Experience with edge and embedded inference using NVIDIA Jetson, TensorRT, ONNX Runtime, or OpenVINO.

• Familiarity with video streaming and industrial cameras using RTSP, GStreamer, GenICam, or machine vision cameras.

• Experience with MLOps tools such as MLflow, Weights and Biases, DVC, Kubernetes, or model registries.

• Background in industrial, robotics, IoT, or B2B product environments.

• Established public track record through open-source contributions, technical writing, or published work.

🏝️ Benefits

• Competitive salary, aligned with the Amman market for this level.

• Fully remote work setup.

• Genuine ownership of features that impact customers.

• Direct access to the European market and senior technical decision-making.

• Asynchronous written communication as the standard practice.

• Reasonable overlap with the European working hours.

• Small teams, streamlined decision-making processes, and direct access to priority setters.

• Integration of human oversight, data protection, and security into the definition of done.