# Machine Learning Engineering Lead at Echo Neurotechnologies Machine Learning Engineering Lead at Echo Neurotechnologies in San Francisco. Posted August 19, 2026. - Company: Echo Neurotechnologies - Location: San Francisco - Experience: 5+ years - Posted: 2026-08-19 - Apply: https://job-boards.greenhouse.io/echo/jobs/4368052009 - Source: https://jobmagic.ai/jobs/machine-learning-engineering-lead-echo-neurotechnologies-c8k4c7 ## Requirements - Bachelor’s or Master’s degree in Computer Science, Data Science, Biomedical Engineering, or equivalent practical experience. - 5+ years of software engineering experience focusing on building, deploying, and maintaining production machine learning models in cloud environments. - Strong proficiency in Python and modern ML frameworks (e.g. PyTorch) along with experience in cloud-native technologies (e.g. Docker). - Solid foundation in digital signal processing (DSP), time-series analysis, or processing high-dimensional biological/medical sensor data. - Demonstrated understanding of data privacy and security standards for handling PII and PHI (HIPAA, SOC 2). - Excellent communication skills and a track record of driving technical execution independently in a fast-paced environment. ## Description ### Company Overview 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.   ### Team Culture 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. ### Job Description 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. ### Role Responsibilities - **Algorithm Productionization & Cloud Deployment:** Design, build, and deploy scalable ML pipelines and clinical algorithms in the cloud to process real-time and batch neural and contextual data. - **Model Optimization & Validation:** Train, evaluate, and optimize machine learning models for signal processing, feature extraction, and behavior detection while maintaining high sensitivity and specificity. - **Model Deployment & Pipeline Integration: **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. - **Mentorship & Process:** Introduce engineering best practices, including CI/CD pipelines, code reviews, and modular architecture, while coaching and mentoring engineers through regular feedback and technical guidance. - **Team Growth & Leadership:** 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. - **Quality & Regulatory Compliance:** Produce rigorous technical documentation, software design specifications, risk analyses, and validation protocols to support regulatory submissions under strict quality management systems. ### Role Qualifications ### Required Qualifications - Bachelor’s or Master’s degree in Computer Science, Data Science, Biomedical Engineering, or equivalent practical experience. - 5+ years of software engineering experience focusing on building, deploying, and maintaining production machine learning models in cloud environments. - Strong proficiency in Python and modern ML frameworks (e.g. PyTorch) along with experience in cloud-native technologies (e.g. Docker). - Solid foundation in digital signal processing (DSP), time-series analysis, or processing high-dimensional biological/medical sensor data. - Demonstrated understanding of data privacy and security standards for handling PII and PHI (HIPAA, SOC 2). - Excellent communication skills and a track record of driving technical execution independently in a fast-paced environment. ### Preferred Qualifications - Experience developing Software as a Medical Device (SaMD) or clinical decision support algorithms under medical device software lifecycle regulations (IEC 62304, ISO 13485). - Hands-on experience with MLOps tools such as Weights & Biases. - Familiarity with streaming data platforms for real-time sensor processing. - Experience writing Python/C++ bindings or optimizing cloud algorithm latency for real-time applications. ### What We Offer - An opportunity to work on exciting, cutting-edge projects to transform patients’ lives in a highly collaborative work environment. - Competitive compensation, including stock options. - Comprehensive benefits package. - 401(k) program with matching contributions.   ### Equal Opportunity Employer Echo Neurotechnologies is an Equal Opportunity Employer (EOE). We celebrate diversity and are committed to creating an inclusive environment for all employees.   ### Confidentiality All applications will be treated confidentially. Applicants may be asked to sign an NDA after the initial stages of the interview process.