Project Engineer, AI Engineer
Listed on 2026-02-16
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IT/Tech
AI Engineer, Machine Learning/ ML Engineer -
Engineering
AI Engineer
Join an extraordinary team in a rapidly evolving industry!
Clear Object has been a pioneer in driving digital innovation for over a decade. We specialize in leveraging cutting-edge technologies such as edge-based artificial intelligence (AI), generative AI, Computer Vision, and Cloud solutions to transform raw data into actionable intelligence. Our solutions empower businesses across diverse industries to optimize operations, elevate customer experiences, and achieve sustainable growth.
As a proud Google Premier Partner, Google GenAI Launch Partner, AWS Select Partner, and IBM Gold Business Partner, we are committed to driving environmental sustainability through our projects, ensuring that every contribution makes a positive impact.
Job SummaryWe are seeking a highly motivated and experienced Project Engineer to join our growing team focused on building and deploying advanced AI/ML solutions. In this role, you will bridge the gap between complex engineering concepts and successful project execution, specifically focusing on cutting‑edge Artificial Intelligence (AI), Machine Learning (ML), and Machine Vision initiatives. You will be responsible for supporting the full lifecycle of technical projects, from initial system architecture design to hardware integration and networking setup.
This is an ideal role for a technical professional with a strong foundational knowledge of hardware/software systems who is eager to specialize in the AI/ML space.
Collaborate with cross‑functional teams, including data scientists and AI/ML engineers, to define project requirements and specifications for platforms supporting AI/ML initiatives.
Design and develop system architectures, including hardware and software components, to meet project needs and ensure seamless integration with the AI/ML platform.
Create detailed documentation, including system diagrams, network topologies, and installation procedures.
Hardware Procurement and ConfigurationResearch, select, and procure appropriate hardware components (cameras, lenses, lighting, processing units, etc.) that meet the performance and scalability requirements of AI/ML workloads.
Configure and test hardware components to ensure compatibility and optimal performance within the AI/ML platform ecosystem.
Manage hardware installations and upgrades, including on‑site support.
Software and Network IntegrationIntegrate software with existing production systems, databases, and the AI/ML platform.
Work with customers to configure network connectivity and security for machine vision systems, ensuring secure data transfer and communication with the AI/ML platform.
Troubleshoot and resolve software and network‑related issues.
Project CoordinationCollaborate with project teams on project plans, timelines, and budgets for machine vision projects within the broader AI/ML initiative.
Coordinate with internal and external stakeholders to ensure successful project execution and alignment with AI/ML goals.
Required QualificationsEducation:
Bachelor’s degree in Electrical Engineering, Computer Engineering, or a related field.
Experience:
3+ years of experience in a technical role, designing and implementing systems, preferably with experience in supporting AI/ML or machine vision projects.
Hands‑on experience with hardware selection, installation, configuration, and troubleshooting in the context of AI/ML systems. Familiarity with industrial automation systems is a plus.
Proficiency in network configuration, protocols (TCP/IP), and managing interconnected systems, including troubleshooting, security practices, and device interoperability.
Experience with project management methodologies and tools.
Preferred Skills & Experience Machine Vision- Understanding of machine vision principles, techniques, and common algorithms.
- Experience with machine vision software libraries and frameworks (e.g., OpenCV, Tensor Flow, PyTorch).
- Familiarity with image processing, analysis, and object recognition techniques.
- Experience with camera selection, calibration, and integration.
- Knowledge of different lighting techniques and their impact on image quality.
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