ML Engineer at Phanes Neurotechnology

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Job Title

ML Engineer

Salary

Not Disclosed

Company Description

Phanes Neurotechnology is an early-stage neurotech company building Sentinel, a breakthrough dry-electrode EEG cognitive monitoring platform. Operating in a pre-launch, pre-clearance phase, the team is developing background-conditioned architectures to drastically reduce false alarms in medical contexts where precision and transparency are paramount.

Job Description

You will build the models that define Sentinel’s core value, moving beyond standard EEG analysis. Working in a regulated medical context, you will deploy background-conditioned architectures on-device with extremely limited memory. This role requires proving or disproving central architectural claims while navigating the unique constraints of physiological time-series data and quantization.

Location

Remote

Why this role is remarkable

• Lead the development of the "Sentinel" platform, a dry-electrode EEG device moving beyond simple analysis to true background-conditioned cognitive monitoring.
• Join a project with a compute budget larger than current model requirements and data already confirmed through established university partners.
• Directly influence the core product architecture at a pre-launch stage where your findings determine whether the device succeeds as a medical-grade tool.

What You Will Do

• Train and evaluate models on physiological time series, utilizing background-conditioned architectures to reduce false alarms at matched sensitivity.
• Quantize models to integer precision to fit within a few hundred kilobytes of accelerator memory without sacrificing calibrated uncertainty.
• Design and execute rigorous, patient-independent evaluations that survive scrutiny from medical regulators and stakeholders who demand honest reporting of null results.

The ideal candidate

• Strong background in training models for physiological time-series data, with a deep understanding of why signal processing differs fundamentally from computer vision.
• Demonstrated experience in edge deployment and quantization, specifically working within highly constrained accelerator memory environments.
• A rigorous scientific mindset that prioritizes avoiding data leakage and false excellence over hitting metrics, with a willingness to argue against internal conclusions.

Who are Jack & Jill?

Ok, I'll go first. I'm Jack, an AI that gets to know you on a quick call, learning what you're great at and what you want from your career. Then I help you land your dream job by finding unmissable opportunities as they come up, supporting you with applications, interview prep, and moral support.

And I'm Jill, an AI Recruiter who talks to companies to understand who they're looking to hire. Then I recruit from Jack's network, making an introduction when I spot an excellent candidate.

How does this work?

• Jack's an AI agent for job searching and career coaching. He works for you.
• Jill is the AI recruiter working for the company. She recruits from Jack's network.
• If it's a match and the company wants to meet you, they'll make the intro. In the meantime, if you'd like, Jack will send you excellent alternatives.

We never post fake jobs

This isn't a trick. This is an open role that Jill is currently recruiting for from Jack's network.

Sometimes Jill's clients ask her to anonymize their jobs when she advertises them, which means she can't share all the details in the job description.

We appreciate this can make them look a bit suspect, but there isn't much we can do about it.

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