AI Hardware-Optimized Algorithms Engineer (Remote)

Jobgether; Oregon; Hybrid; USD 130,000 - 210,000; Full time

Benefits offered by this job

Remote flexibility

Meaningful technical impact

Challenging engineering work

Collaborative culture

Professional growth

Engineering ownership

Job summary

Partner Company in the United States seeks an AI Algorithms/Software Engineer to design and optimize neural network algorithms for deployment on specialized analog hardware. You will collaborate across software, AI, and hardware teams to improve accuracy, latency, and efficiency.

You will work on quantization-aware training, model simulation of hardware effects, and robust software tooling in a remote-friendly environment. A strong background in PyTorch and ONNX is preferred.

Qualifications

• Bachelor's degree in Computer Science, Mathematics, or a related technical field.
• At least five years of professional software engineering experience in a production environment.
• Strong programming, analytical, debugging, and problem-solving skills.
• Experience with PyTorch and model interoperability with ONNX is an advantage.
• Experience with hardware-aware machine learning techniques (quantization, pruning, QAT) is a plus.
• Familiarity with ML operations (CI/CD, deployment, monitoring) is beneficial.
• A master's degree or PhD is desirable.
• Curiosity, adaptability, and collaborative mindset are important.

Responsibilities

• Design, develop, and optimize algorithms and software tools for neural network conversion, adaptation, and deployment on specialized analog computing hardware.
• Improve AI software pipelines to enhance model accuracy, latency, computational efficiency, and usability.
• Develop quantization-aware and analog-aware training techniques to improve neural network performance under hardware constraints.
• Build models that simulate analog hardware effects and evaluate their impact on neural network behavior.
• Implement network regularization and other optimization techniques to improve robustness.
• Collaborate with hardware and software engineers across teams.
• Contribute to hardware co-design by providing software insights and performance evaluations.
• Strengthen software quality through refactoring, automated testing, and documentation.
• Monitor advances in deep learning to identify opportunities for improvement.

Skills

5+ years exp

PyTorch familiarity

ONNX interoperability

Hardware-aware ML

Quantization-aware training

C++ / Python

MLOps basics

Open-source contributions

Education

Bachelor's degree in CS/Math

Master's or PhD desirable

Tools

PyTorch

ONNX

Job description

Partner Company in the United States seeks an AI Algorithms/Software Engineer to design and optimize neural network algorithms for deployment on specialized analog hardware. You will collaborate across software, AI, and hardware teams to improve accuracy, latency, and efficiency.

You will work on quantization-aware training, model simulation of hardware effects, and robust software tooling in a remote-friendly environment. A strong background in PyTorch and ONNX is preferred.