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# Machine Learning Engineer

- **Company:** NUDGE LLC
- **Location:** San Francisco, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Computer Vision, Code Review, Imaging Technology, Python (Programming Language), Machine Learning, Signal Processing, Information Technology
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/machine-learning-engineer-nudge-8302614

## About the Role

We are looking for engineers with at least 3 years of industry experience. Regardless of career level, you should have:

 * Strong first-principles understanding of engineering, physics, and signal processing.
 * Experience writing production-level code (Python preferred)
 * A degree in Computer Science or similar engineering discipline
 * You do not need prior experience with ultrasound or neuroscience
 * Shipped products that deliver value in the real world; ideally, you will have solved problems involving messy real-world sensors
 * High integrity and strong professional judgement

## Description

As a Machine Learning Lead at Nudge, you will drive the development of next-generation ML and imaging systems at the intersection of ultrasound, signal processing, and neuroscience. You'll lead technical direction across core ML initiatives while remaining deeply involved in architecture, modeling, and deployment.

In this role, you will:

 * Lead the design and development of imaging algorithms that leverage in-house ultrasound transducers and high-performance compute to image the brain and skull
 * Drive the development of high-resolution acoustic simulation systems to model the propagation and scattering of ultrasound energy and accurately predict delivered dose
 * Architect computer vision and real-time inference systems that track brain motion and dynamically adapt targeting parameters during treatment
 * Partner closely with mechanical engineers, electrical engineers, ultrasound engineers, transducer designers, and neuroscientists to translate research concepts into robust production systems
 * Define technical strategy and best practices across machine learning, modeling, simulation, and signal processing infrastructure
 * Mentor and elevate other engineers through technical leadership, code review, and systems-level thinking
 * Help shape the long-term ML roadmap as we apply machine learning in a domain where it has not traditionally been used


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