Data Scientist Edge AI & Embedded Systems

Vantor seeks a Data Scientist focused on Edge AI and Embedded Systems to build efficient ML solutions for constrained devices. You'll design and optimize models for on device inference, develop data and deployment pipelines, and collaborate with engineers to integrate AI into modern software and hardware products. Using Python, deep learning frameworks, and embedded tooling, you'll tackle real time analytics, optimization for latency and power, and MLOps for fleets of devices. Join a collaborative, low ego team delivering scalable, data driven solutions for impactful client projects.

Responsibilities

• Design, train, and deploy machine learning models optimized for edge and embedded devices

• Develop efficient inference pipelines for real-time analytics on constrained hardware

• Collaborate with software and firmware engineers to integrate AI into embedded products

• Optimize models for latency, memory, and power consumption using pruning, quantization, and compression

• Build data pipelines and perform feature engineering to support production models

• Implement MLOps practices for monitoring, versioning, and updating edge models

• Work with clients to translate business problems into edge AI solutions and prototypes

• Document architectures, experiments, and deployment procedures for maintainability Required Skills

• Python

• Machine learning

• Deep learning (Tensor

• Flow/Py

• Torch)

• Edge AI/embedded ML (Tensor

• Flow Lite, ONNX Runtime, etc.)

• Embedded systems development (C/C++)

• Model optimization and quantization

• Data engineering and pipelines

• Cloud platforms (AWS/Azure/GCP)

• MLOps for edge deployments

• Linux and containerization