<p><strong>About Arcanys</strong></p><p>Arcanys launched in 2010 to help entrepreneurs and innovators from Australia, Europe and other parts of the globe accelerate their software development with dedicated remote engineers from the Philippines (and, more recently, Bulgaria).</p><p><strong>Why work with us?</strong></p><p>There’s a unique spirit to Arcanys—manifested in our amazing talents, passion for technology, and a strong focus on everyone’s career and personal development. As a company rooted in people, we make a point to offer exciting work opportunities and foster a culture that everyone can meaningfully contribute to.</p><p>Join us as a: <strong>Applied ML Scientist, Digital Biomarker</strong><br><br>Works alongside our SDSC data-science partners and in-house science and backend teams.</p><p>As an Applied ML Engineer on the MSI team, you develop the statistical and machine learning models that turn behavioral app data into a validated digital biomarker of craving. From exploratory analysis and feature engineering to production deployment and monitoring, you will own the full machine learning lifecycle and work closely with backend and frontend engineers to bring AI-powered features to our platform.<br></p><p><strong>In this role you’ll get to:</strong></p><ul><li><p>Develop and implement statistical and machine learning models on behavioral and response-time data from in-app tasks.</p></li><li><p>Engineer features from high-frequency behavioral data and identify the most informative signals through statistical analysis.</p></li><li><p>Benchmark model families from regularized statistical models and gradient-boosted trees (XGBoost, LightGBM).</p></li><li><p>Design and run validation: cross-validation, calibration, explainability (SHAP), feature-importance and ablation analysis, with a focus on out-of-sample generalization.</p></li><li><p>Build and maintain reproducible training pipelines, experiment tracking, and model versioning using modern MLOps practices.</p></li><li><p>Deploy models as scalable APIs and collaborate with backend engineers to integrate them into production and optimize them for low-latency, on-device inference where appropriate.</p></li><li><p>Monitor model performance, data quality, and model drift, and continuously improve production models.</p></li><li><p>Help define the company’s machine learning architecture, engineering standards, and technical roadmap.</p></li><li><p>Collaborate with product, engineering, and clinical stakeholders to translate real-world problems into practical ML solutions.</p></li><li><p>Keep the modelling pipeline extensible to new modalities (wearables for HRV and GSR, pupillometry, EEG).<br></p></li></ul><p><strong>What you’ll need to succeed:</strong></p><ul><li><p>Background in statistics, data science, machine learning, computational neuroscience, biomedical engineering, applied mathematics, or a related quantitative discipline.</p></li><li><p>Around 3-6+ years developing and deploying ML solutions, ideally on behavioral, sensor, or physiological-signal data.</p></li><li><p>Strong understanding of applied statistics, feature engineering, supervised learning, model evaluation, and explainability.</p></li><li><p>Fluent in Python and the scientific Python ecosystem, including Pandas or Polars, NumPy, and scikit-learn.</p></li><li><p>Experience building production-quality software with Git, Docker, REST APIs (FastAPI or similar), and CI/CD workflows.</p></li><li><p>A track record of models that generalize, with disciplined validation and overfitting control.</p></li><li><p>Pragmatic, product-oriented mindset with an emphasis on delivering maintainable, production-ready solutions rather than research prototypes.</p></li><li><p>Comfortable working with health data and its privacy requirements (GDPR).<br></p></li></ul><p><strong>It’s Great if you have:</strong></p><ul><li><p>Experience developing digital biomarkers or digital therapeutics.</p></li><li><p>Experience with MLOps tools such as MLflow, Dagster, Airflow, or similar platforms.</p></li><li><p>Experience deploying models on cloud infrastructure (AWS, OpenStack, Kubernetes, or Docker).</p></li><li><p>Experience developing digital biomarkers or digital therapeutics.</p></li><li><p>Experience optimizing models for mobile or edge-device inference.<br></p></li></ul><p><strong>The Perks:</strong></p><p>We like to make sure the talent is well taken care of, and here are just some of the benefits you will enjoy:</p><ul><li><p>Top compensation based on expertise – we are only looking for top talent and pay accordingly.</p></li><li><p>Long-term work from home + allowances - we let you work from the comfort of your home + amazing allowances you get to enjoy!</p></li><li><p>Reimbursable allowance of up to 15K for your home office setup</p></li><li><p>Standard 5 day work week from Monday to Friday.</p></li><li><p>Flexible working schedule. You can choose your working hours (within reason).</p></li><li><p>Flat management style and open-door policy - no micromanagement and your voice is being heard!</p></li><li><p>Work with the latest technologies - you can hone your skills and work with Australian and European clients + a chance to earn more through our self-training program.</p></li><li><p>Enrolment to HMO for a maximum of 3 immediate dependents on your 1st day.</p></li><li><p>Incentive-based wellness program.</p></li><li><p>Toastmasters, English classes, and other learning opportunities.</p></li><li><p>Free consultations with Arcanys registered nutritionist-dietitians.</p></li><li><p>Free access to our very own Arcanys CrossFit gym (or get a company-sponsored membership in a different gym, whichever suits your needs best).</p></li></ul>