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Machine Learning Engineer (Edge AI & Computer Vision)

Role overview

Qualifications

  • Strong experience bringing AI to production
  • Solid background in AI & Deep Learning
  • Edge AI & Embedded exposure
  • Advanced English level

Responsibilities

  • Take end-to-end ownership of Machine Learning models
  • Design, build, and optimize real-time AI pipelines
  • Optimize inference performance for Edge AI platforms
  • Collaborate with clients and cross-functional teams

About the company

Marvik logo

Marvik

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Company details

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Job description

Want to work with cutting-edge technologies on long-term, strategic projects that combine Deep Learning, Computer Vision, Edge AI, and IoT? 🚀🤖🚜

At Marvik, we are leading the next evolution of smart machinery—integrating vision capabilities, real-time image processing, and multi-sensor fusion into physical products operating in real environments.

🌟 What do we offer?:

  • Challenging, real-world projects: Work on stuff other people only read about—bringing AI out of the cloud and straight into physical, intelligent machinery.

  • State-of-the-art tech stack: Optimize and deploy cutting-edge Computer Vision and Deep Learning models on Edge devices.

  • Strategic growth: Join an expanding team with huge potential for long-term ownership, leadership, and professional development.

  • Great team culture: Excellent work environment full of highly motivated, collaborative, and talented professionals who elevate each other.

  • Global exposure & On-site experiences: Opportunity to travel internationally to work directly with clients.

  • Flexible work style: Opportunity to work remotely with global, high-impact clients.

🧑🏻‍💻 Responsibilities:

  • Take end-to-end ownership of Machine Learning models, moving them beyond training and ensuring reliable deployment in production on physical hardware.

  • Design, build, and optimize real-time AI pipelines, integrating foundation models, sensor and application data, and scalable inference workflows.

  • Optimize inference performance, memory usage, and execution speed for Edge AI platforms (e.g., NVIDIA Jetson, embedded platforms).

  • Collaborate directly with clients and cross-functional engineering teams, building trust, proposing proactive solutions, and maintaining smooth technical communication.

  • Debug, monitor, and maintain production models operating continuously under real-world hardware constraints.

🤝 If you have:

  • Strong experience bringing AI to production: It’s not just about training models—you know how to make them run reliably in real-world environments.

  • Solid background in AI & Deep Learning, including experience with LLMs, Computer Vision, multimodal models, model optimization, and efficient inference.

  • Edge AI & Embedded exposure: Experience optimizing models for constrained devices (TensorRT, ONNX, OpenCV, C++, or Python).

  • Strong Ownership & Soft Skills: Highly collaborative, proactive, independent, and clear in technical communication. A team player who builds trust with clients and peers.

  • Advanced English level: Excellent verbal and written communication skills to interact directly with international client teams.

  • Required tools: Python, C++, PyTorch/TensorFlow, OpenCV, Docker, Git.

🦾 It’s a major plus:

  • Hands-on experience with NVIDIA Jetson, ROS/ROS2, or embedded hardware platforms.

  • Experience in domains such as Robotics, IoT, Drones, Automotive, or Industrial Machinery.

  • Knowledge of sensor fusion (IMU, cameras, LiDAR) or OTA (Over-The-Air) updates and Cloud IoT architectures (AWS/Azure IoT).

Apply once. Then go straight to the hiring manager.

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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