- Company Name
- IRVINEi
- Job Title
- Senior AI Engineer
- Job Description
-
**Job title:** Senior AI Engineer
**Role Summary:** Lead the development, optimization, and deployment of computer vision solutions for edge and cloud environments while integrating advanced large language models and multi‑agent systems.
**Expectations:**
- Design innovative CV strategies and LLM integrations that meet performance, accuracy, and scalability targets.
- Mentor junior engineers and drive best practices in model engineering and software development.
- Collaborate with cross‑functional teams to translate business requirements into robust AI products.
**Key Responsibilities:**
- Design, develop, and deploy facial and object recognition models for edge devices and cloud/servers.
- Integrate LLMs into multi‑agent applications, ensuring effective interfacing and data flow.
- Optimize CV models for speed, accuracy, and resource efficiency, using techniques such as quantization and pruning.
- Implement image‑processing pipelines for feature extraction, detection, pose estimation, segmentation, and classification.
- Build inference APIs with Flask or FastAPI, incorporating multithreading/asynchronous patterns for high throughput.
- Collaborate with frontend and backend teams to embed ML capabilities into web services.
- Conduct experiments, evaluate model metrics, and iterate designs to meet target performance.
- Stay current with emerging CV and LLM research and tools, applying relevant advances to internal solutions.
- Provide technical guidance, conduct code reviews, and facilitate knowledge sharing within the team.
**Required Skills:**
- 5+ years’ experience in computer vision application development.
- Proven track record of deploying CV models on edge devices (e.g., NVIDIA Jetson, Coral) and cloud/servers.
- Deep knowledge of modern LLMs (e.g., GPT, LLaMA) and experience building multi‑agent systems.
- Strong proficiency in Linux, Python, Flask, FastAPI, and asynchronous programming.
- Hands‑on experience with object‑detection architectures (YOLO, SSD, Faster R‑CNN), segmentation, and tracking.
- Advanced image‑processing expertise using OpenCV, TensorFlow/PyTorch, and related libraries.
- Familiarity with version control (Git), CI/CD pipelines, and containerization (Docker, Kubernetes).
- Experience with AI frameworks/tools such as CrewAI, Lagchain, Selenium, and other deep‑learning libraries.
- Excellent problem‑solving, communication, and collaborative skills.
**Required Education & Certifications:**
- Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related technical field.
- Relevant certifications in machine learning, deep learning, or cloud platforms (e.g., AWS ML, Google Cloud AI) are advantageous but not mandatory.