ML Algorithm Engineer — Embedded Hardware Deployment

Aditi Consulting; Redmond (WA); On-site; USD 113,000 - 118,000; Full time

Benefits offered by this job

Medical, dental, and vision

Health savings accounts

Paid time off

Bereavement leave

401(k) with employer match

Life and disability insurance

Commuter benefits

Dependent care FSA

Accident insurance

Critical illness insurance

Hospital indemnity insurance

Accommodations for work travel

Performance bonus

Job summary

Aditi Consulting in Redmond, WA is seeking an algorithm developer to design and implement ML algorithms and deploy them to embedded hardware. You will test, optimize, and port code to firmware, working with PyTorch/TensorFlow, Python, and C on ARM/NVidia Jetson/RPi platforms, with on-site support in Redmond.

Join a team that delivers practical ML solutions for hardware, focusing on performance, reliability, and scalable firmware integration.

Qualifications

• Experience building ML models and pipelines for hardware deployment.
• Proficient in C or similar OOP languages for embedded systems.
• Experience with ML toolkits and platforms.

Responsibilities

• Train and optimize ML/hybrid pipelines for hardware deployment.
• Develop and apply deep learning algorithms.
• Design, implement, and test ML algorithms.
• Model workload performance statistically.
• Synthesize algorithm needs for customer requirements.
• Identify, troubleshoot, and resolve software issues.
• Deploy algorithms to hardware and improve performance.

Skills

Python

ML Algorithms

AI usage

Embedded system knowledge

ARM CPU-NPU

Firmware understanding

Tools

PyTorch

TensorFlow

Job description

Aditi Consulting in Redmond, WA is seeking an algorithm developer to design and implement ML algorithms and deploy them to embedded hardware. You will test, optimize, and port code to firmware, working with PyTorch/TensorFlow, Python, and C on ARM/NVidia Jetson/RPi platforms, with on-site support in Redmond.

Join a team that delivers practical ML solutions for hardware, focusing on performance, reliability, and scalable firmware integration.