Role overview
A spinout from PsychoGenics Inc, Axelyra is a well-funded, biotech startup focused on unmet needs in psychiatric and neurological disorders. We leverage proprietary preclinical platforms and AI-driven analytics spanning both clinical and preclinical behavioral and electrophysiological (EEG) phenotyping to enable a compound re-innovation strategy.
We are building AI-enabled platforms that support clinical development, including tools and models that help quantify treatment response, stratify patients, and accelerate learning across trials. Our work is highly multidisciplinary, with day-to-day collaboration across data science/engineering, biologists, translational scientists, and clinicians.
PsychoGenics is a preclinical CRO with expertise in central nervous system (CNS) and orphan disorders. PsychoGenics is known for it's cutting-edge translational approach to research, customized solutions, the breadth, and quality of our work, as well as for our ability to identify statistically relevant phenotypic changes that help clients quantify the efficacy of their treatments. With an extensive portfolio of highly predictive disease models and unparalleled experience performing studies for biopharmaceutical companies of all sizes, we enable clients to deliver much needed superior clinical candidates to patients.
What you'll work on
- Train, optimize, and deploy ML/DL models into production workflows.
- Integrate models into existing data processing pipelines (preclinical + clinical).
- Build ETL/data pipelines and data QC tooling for EEG/behavioral modalities.
- Develop APIs and services that power internal analytics and trial-facing platforms.
- Partner with scientists, biologists, and clinicians to productionize models (monitoring, performance, drift, reliability).
What we're looking for
- Bachelor’s degree in computer science, Software Engineering, Electrical Engineering, Statistics, Mathematics, or a related field. Master’s degree is a plus.
- Proficiency in Python; working knowledge of C++, C#, or Java.
- Experience with cloud computing (AWS, Azure, or GCP).
- Experience with deployment tools (e.g., Docker).
- Experience with computer vision and time-series data.
- Familiarity with biomedical context and/or interpretation of biological/clinical data.
- Collaborative, driven with experience working in a fast-paced start-up environment.
- Excellent analytical and problem-solving skills, with the ability to deeply understand the "why" and "how" of our work.
- Strong communication and teamwork abilities.
Salary will be determined by factors including job-related skills, experience, knowledge, education and geographic location.