Machine Learning Engineer (Edge AI & Computer Vision)
Marvik · Buenos Aires, Argentina
Information Technology & Services · 51-200 employees
About the role
You will take end-to-end ownership of machine learning models, ensuring their reliable deployment and performance on physical hardware. Additionally, you will design and optimize real-time AI pipelines while collaborating with cross-functional teams and clients.
What they look for
Requirements
Candidates must have strong experience in bringing AI to production and optimizing models for edge devices using tools like Python, C++, and PyTorch. Excellent English communication skills and a proactive, collaborative mindset are essential for this role.
Benefits
Full 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.
- 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).
