Machine Learning Algorithm Engineer

Job Title: Machine Learning Algorithm Engineer

Location: Redmond, WA (Hybrid - 3 Days Onsite)

Duration: 12-Month Contract (Potential for Extension)

We are seeking a Machine Learning Algorithm Engineer to join an innovative research and engineering team focused on intelligent sensing systems, machine learning, and hardware-integrated AI solutions. This role involves developing, optimizing, and deploying machine learning algorithms that operate on real-world sensor data and support the development of advanced prototype systems.

The ideal candidate combines strong Python development skills with hands-on experience in machine learning, deep learning frameworks, and deploying AI solutions to hardware platforms

Responsibilities

Design, develop, test, and optimize machine learning and deep learning algorithms.

Build and improve ML pipelines for deployment on hardware platforms.

Develop statistical models and algorithms for data analysis and performance optimization.

Train, evaluate, and fine-tune machine learning models using modern ML frameworks.

Troubleshoot and resolve software and algorithm performance issues.

Collaborate with multidisciplinary engineering teams to develop prototype solutions.

Deploy AI and machine learning solutions to embedded and edge-computing environments.

Improve software efficiency, scalability, and deployment workflows.

Work independently to execute projects from concept through implementation.

Required Qualifications

Bachelor's degree in Computer Science, Mathematics, Electrical Engineering, Robotics, or a related technical field. Master's degree preferred.

1-6 years of professional experience in machine learning, AI, software engineering, or algorithm development.

Strong programming skills in Python.

Experience developing machine learning and deep learning algorithms.

Hands-on experience with PyTorch and/or TensorFlow.

Experience with object-oriented programming using C++ or similar languages.

Familiarity with AI-assisted development tools and workflows.

Ability to work independently in a research-oriented environment.

Preferred Qualifications

Experience with embedded systems and edge-computing platforms.

Experience deploying machine learning models to hardware environments.

Understanding of firmware concepts and hardware/software integration.

Experience working with ARM-based computing architectures and AI accelerators.

Knowledge of machine learning deployment optimization techniques