About the Role
We are looking for a Senior Machine Learning Engineer / MLOps Engineer to own the end-to-end production lifecycle of our ML models for our medical device, Brain20. In this role, you will bridge the gap between initial research concepts and robust, production-ready systems. You will take ownership of taking algorithms from early-stage research/definition, refactoring and optimizing them, and deploying them onto both physical edge devices and AWS cloud infrastructure.
Responsibilities
•Own the complete ML lifecycle—taking models from early-stage definition through refactoring, optimization, packaging, and deployment.
•Deploy, run, and optimize ML models on our physical medical device (Brain20) as well as AWS cloud infrastructure.
•Elevate experimental Python codebases into highly maintainable, efficient, concurrent, and thoroughly tested production software.
•Design, build, and maintain robust CI/CD pipelines and deployment strategies tailored for medical software standards.
•Translate experimental algorithms provided by neuroscience researchers into clean, high-performance, and scalable production code.
Requirements
•6+ years of professional software engineering experience in commercial environments (tech startups/scale-ups), with a strong track record of taking ML models into production.
•Proven ability to manage the complete lifecycle of ML models in production environments.
•Practical experience deploying models onto physical/embedded hardware (Edge AI) and AWS cloud infrastructure.
•Deep expertise in Python (concurrency, parallelization, memory management, profiling, and packaging).
•Clear theoretical understanding of machine learning fundamentals and deep learning architectures.
•Pragmatic & product-oriented analytical problem solver.
•Autonomous & collaborative.
•Fluent English.
•Immediate or short notice period preferred.
Nice to Have
•Experience processing EEG, SSEP, or biosignal/time-series data.
•Familiarity with software development under medical device standards (e.g., ISO 13485, IEC 62304) or data privacy regulations (GDPR/HIPAA).
•Experience with model optimization techniques for edge devices (quantization, ONNX, TensorRT).
Conditions
No conditions were specified in the posting.
