Machine Learning Engineer

BS, MS, or PhD in Computer Science, Electrical Engineering, Applied Mathematics, Machine Learning, AI, Robotics, or a related field.

Strong hands-on programming experience in C++ and Python.

3-5 years of experience developing and deploying machine learning systems in production environments.

Experience building AI agents, LLM-based applications, or intelligent automation systems.

Strong problem-solving skills and ability to work across the full development lifecycle.

Excellent written and verbal communication and collaboration skills.

Enjoys solving difficult technical challenges that span algorithms, software, and deployment.

Enjoys bridging the gap between research and production, finding practical engineering solutions that make advanced ML usable in real-world products.

Takes ownership and drives projects from concept through production.

Continuously explores new AI, ML, and agentic technologies.

Works effectively across multidisciplinary teams.

Balances research innovation with practical product delivery.

Builds side projects, experiments with emerging AI tools, or enjoys hands-on technical exploration.

Experience with radar, RF sensing, sensor fusion, computer vision, robotics, or autonomous systems.

Experience with LangChain, LangGraph, LlamaIndex, AutoGen, Semantic Kernel, or similar frameworks.

Experience optimizing models for edge deployment usingTensorRT, ONNX,OpenVINO, TVM, or similar tools.

Experience with embedded systems, GPUs, NPUs, FPGAs, or hardware acceleration.

Familiarity withMLOps, CI/CD, model monitoring, and large-scale production systems.

At MatrixSpace, Machine Learning Engineering is where advanced AI research becomes real-world capability. This is an engineering-heavy ML role focused on productionizing algorithms created by Data Scientists, with some ownership of the ML infrastructure that helps those Data Scientists move faster.