Machine Learning Engineering Lead

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<div class="content-intro"><h2 data-pm-slice="1 1 []">Company Overview</h2>
<p>Echo Neurotechnologies is an exciting new startup in the Brain-Computer Interface (BCI) space, driving innovation through advanced hardware engineering and AI solutions. Our mission is to deliver cutting-edge technologies that restore autonomy to people living with disabilities and improve their quality of life.</p>
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<h2>Team Culture</h2>
<p>Join a small, dedicated team of knowledgeable and motivated professionals. Our early-stage environment offers the opportunity to take ownership of broad decisions with significant and long-lasting impact. We emphasize continuous learning and growth, fostering cross-functional collaboration where your contributions are vital to our success.</p></div><h2>Job Description</h2>
<p>We are seeking a Machine Learning Engineering Lead to design, scale, and deploy clinical-grade ML algorithms in the cloud. In this role, you will initially operate as a high-impact individual contributor, and as the platform matures, you will expand and lead a dedicated team of machine learning engineers, shaping both the technical roadmap and day-to-day execution. You will take ownership of translating complex, neurophysiological signals into production-ready predictive models and automated diagnostic features. You will design, build and deploy cloud-based models, ensuring data is processed with high reliability, low latency, and strict regulatory compliance.</p>
<h2>Role Responsibilities</h2>
<ul>
<li><strong>Algorithm Productionization &amp; Cloud Deployment:</strong> Design, build, and deploy scalable ML pipelines and clinical algorithms in the cloud to process real-time and batch neural and contextual data.</li>
<li><strong>Model Optimization &amp; Validation:</strong> Train, evaluate, and optimize machine learning models for signal processing, feature extraction, and behavior detection while maintaining high sensitivity and specificity.</li>
<li><strong>Model Deployment &amp; Pipeline Integration: </strong>Architect scalable pipelines to deploy and integrate production models into the cloud environment, managing model automated training, data versioning, and performance monitoring, in collaboration with a platform team.</li>
<li><strong>Mentorship &amp; Process:</strong> Introduce engineering best practices, including CI/CD pipelines, code reviews, and modular architecture, while coaching and mentoring engineers through regular feedback and technical guidance.</li>
<li><strong>Team Growth &amp; Leadership:</strong> Build and scale a high-performing ML engineering team from the ground up, transitioning into a direct line management role to lead technical strategy, resource planning, and day-to-day execution.</li>
<li><strong>Quality &amp; Regulatory Compliance:</strong> Produce rigorous technical documentation, software design specifications, risk analyses, and validation protocols to support regulatory submissions under strict quality management systems.</li>
</ul>
<h2>Role Qualifications</h2>
<h3>Required Qualifications</h3>
<ul>
<li>Bachelor’s or Master’s degree in Computer Science, Data Science, Biomedical Engineering, or equivalent practical experience.</li>
<li>5+ years of software engineering experience focusing on building, deploying, and maintaining production machine learning models in cloud environments.</li>
<li>Strong proficiency in Python and modern ML frameworks (e.g. PyTorch) along with experience in cloud-native technologies (e.g. Docker).</li>
<li>Solid foundation in digital signal processing (DSP), time-series analysis, or processing high-dimensional biological/medical sensor data.</li>
<li>Demonstrated understanding of data privacy and security standards for handling PII and PHI (HIPAA, SOC 2).</li>
<li>Excellent communication skills and a track record of driving technical execution independently in a fast-paced environment.</li>
</ul>
<h3>Preferred Qualifications</h3>
<ul>
<li>Experience developing Software as a Medical Device (SaMD) or clinical decision support algorithms under medical device software lifecycle regulations (IEC 62304, ISO 13485).</li>
<li>Hands-on experience with MLOps tools such as Weights &amp; Biases.</li>
<li>Familiarity with streaming data platforms for real-time sensor processing.</li>
<li>Experience writing Python/C++ bindings or optimizing cloud algorithm latency for real-time applications.</li>
</ul><div class="content-conclusion"><h2 data-pm-slice="1 1 []">What We Offer</h2>
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<p>An opportunity to work on exciting, cutting-edge projects to transform patients’ lives in a highly collaborative work environment.</p>
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<p>Competitive compensation, including stock options.</p>
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<p>Comprehensive benefits package.</p>
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<p>401(k) program with matching contributions.</p>
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</ul>
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<h2>Equal Opportunity Employer</h2>
<p>Echo Neurotechnologies is an Equal Opportunity Employer (EOE). We celebrate diversity and are committed to creating an inclusive environment for all employees.</p>
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<h2>Confidentiality</h2>
<p>All applications will be treated confidentially. Applicants may be asked to sign an NDA after the initial stages of the interview process.</p></div>

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