(Senior) ML Engineer

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    "description": "<p><span style=\"font-size: 10pt\">Clue is more than just a place to work. Our work empowers women and people with cycles to make more informed decisions about their health. We break down barriers, myths, and taboos. Our workplace is agile, diverse, and full of growth opportunities.</span></p>\n<p><span style=\"font-size: 10pt; font-weight: bold\"><br>A NOTE FROM YOUR TEAM</span></p>\n<p><span style=\"font-size: 10pt\">As a (Senior) Machine Learning Engineer, you will play a key role in shaping how applied machine learning is responsibly built and operated at Clue. The role is based in the data team and works cross-functionally with science, product, and platform teams.</span></p>\n<p><span style=\"font-size: 10pt\">You will work on science-based ML use cases grounded in longitudinal and sparse health data, contributing to user-facing features that require a high bar for correctness, safety, and regulatory compliance.</span></p>\n<p><span style=\"font-size: 10pt\">You’ll join a purpose-driven, collaborative environment where your technical ownership directly supports Clue’s mission, user trust, and long-term product strategy.</span></p>\n<p><span style=\"font-size: 10pt; font-weight: bold\"><br>WHAT YOU’LL DO</span></p>\n<ul>\n<li><span style=\"font-size: 10pt\">Design, develop, and maintain science-based machine learning models for use cases involving longitudinal and sparse data</span></li>\n<li><span style=\"font-size: 10pt\">Apply scientific reasoning to model design and validation, ensuring modelling assumptions, limitations, and outputs align with current scientific understanding</span></li>\n<li><span style=\"font-size: 10pt\">Work with cycle tracking data, biometric signals, and other health-related data sources to build and evaluate robust models</span></li>\n<li><span style=\"font-size: 10pt\">Translate scientific and research insights into production-ready ML systems in close collaboration with the Science team</span></li>\n<li><span style=\"font-size: 10pt\">Own the end-to-end ML lifecycle, including training, evaluation, validation, deployment, monitoring, and iteration in production</span></li>\n<li><span style=\"font-size: 10pt\">Define and evolve ML operational practices to ensure models are reliable, observable, reproducible, and maintainable over time</span></li>\n<li><span style=\"font-size: 10pt\">Ensure the availability and quality of data inputs, testing datasets, and evaluation pipelines in collaboration with data and engineering teams</span></li>\n<li><span style=\"font-size: 10pt\">Integrate health-specific ML models with other AI components</span></li>\n<li><span style=\"font-size: 10pt\">Ensure ML systems are developed and operated in line with privacy, security, and regulatory expectations (e.g. GDPR, EU AI Act)</span><span style=\"font-size: 10pt\"><br><br></span></li>\n</ul>\n<p><span style=\"font-size: 10pt; font-weight: bold\">WHAT WE’RE LOOKING FOR</span></p>\n<ul>\n<li><span style=\"font-size: 10pt\">Advanced degree (PhD preferred) in Machine Learning, Data Science, Computer Science, or a life sciences discipline (e.g. biology, biomedical sciences), focused on health, biological, or physiological data</span></li>\n<li><span style=\"font-size: 10pt\">Demonstrated ability to apply scientific reasoning to the design, validation, and interpretation of machine learning models, including independent assessment of scientific assumptions and limitations</span></li>\n<li><span style=\"font-size: 10pt\">Academic or applied research experience working with sparse, longitudinal, or health-related data (for example: through a thesis or publications)</span></li>\n<li><span style=\"font-size: 10pt\">Several years of experience applying machine learning in production or production-adjacent environments</span></li>\n<li><span style=\"font-size: 10pt\">Strong grounding in statistical methods and applied machine learning</span></li>\n<li><span style=\"font-size: 10pt\">Hands-on experience with ML Ops practices, including deployment, monitoring, reproducibility, and model lifecycle management</span></li>\n<li><span style=\"font-size: 10pt\">Experience working with cloud-based infrastructure, preferably AWS</span></li>\n<li><span style=\"font-size: 10pt\">Ability to communicate complex technical concepts clearly to cross-functional stakeholders</span></li>\n<li><span style=\"font-size: 10pt\">Experience working in or with regulated environments is a strong plus</span><span style=\"font-size: 10pt\"><br><br></span></li>\n</ul>\n<p><span style=\"font-size: 10pt\">We recognise that strong candidates may not meet every requirement and encourage applications from those with deep scientific and applied ML experience.</span></p>\n<p><br></p>\n<p><span style=\"font-size: 10pt; font-weight: bold\">WORKING AT CLUE</span></p>\n<p><span style=\"font-size: 10pt\">At Clue, we embrace a culture that values diversity, inclusion, and collaboration. We believe in creating a workplace where everyone feels empowered to contribute, grow, and make a difference.</span></p>\n<p><br></p>\n<p><span style=\"font-size: 10pt; font-weight: bold\">What we offer:</span></p>\n<ul>\n<li><span style=\"font-size: 10pt\">27+ days of paid time off</span></li>\n<li><span style=\"font-size: 10pt\">Urban Sports Club membership</span></li>\n<li><span style=\"font-size: 10pt\">Professional &amp; Personal Development: Access to a dedicated development budget and resources to grow in your role</span></li>\n<li><span style=\"font-size: 10pt\">Office Space: A vibrant office in the heart of Berlin, where collaboration and innovation happen</span></li>\n<li><span style=\"font-size: 10pt\">Hybrid Work Model: The flexibility to work from home while maintaining a strong connection with the team</span></li>\n</ul>\n<p><br></p>\n<p><span style=\"font-size: 10pt; font-weight: bold\">GOOD TO KNOW</span></p>\n<p><span style=\"font-size: 10pt; font-weight: bold\">Main Location: </span><span style=\"font-size: 10pt\">Berlin </span></p>\n<p><span style=\"font-size: 10pt; font-weight: bold\">Employment Type:</span><span style=\"font-size: 10pt\"> Full Time</span></p>\n<p><span style=\"font-size: 10pt; font-weight: bold\">Reporting To: </span><span style=\"font-size: 10pt\">Director of Data</span></p>",
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