Data Scientist III - AI & Machine Learning

<div class="content-intro"><h3>ABOUT onX</h3> <p>We’re a team of builders, adventurers, and risk takers using technology to help people confidently explore the outdoors. Driven by our mission to awaken the adventurer inside everyone, we build products that optimize every outdoor experience and inspire confidence to get out and go further.</p> <p>We’re a high-growth tech company. The pace is fast, the work takes grit, and ambiguity is part of the job. As the world changes around us, we adapt - continuously evolving how we build, prioritize, and deliver.</p> <p>Our business moves quickly, and there’s real opportunity to shape what we build next. Each of our verticals - Hunt, Offroad, Backcountry, and Fish - is at a different stage of maturity, which means the challenges you encounter and the impact you have will vary depending on where you sit and what the business needs most.</p> <p>We operate with an experimentation mindset, continually iterating and improving how we solve problems. We expect our people to use the latest tooling, including AI, thoughtfully and responsibly, pairing human judgment with technology to increase quality, speed, and impact.</p> <p>Our impact comes to life through the products we build, in the stories of our customers, and in our growing commitment to land stewardship and recreational access.</p></div><h3>ABOUT THIS OPPORTUNITY</h3> <p>We are looking for a Data Scientist who views machine learning as a product, not just a research project. You will be a foundational member of our AI team, responsible for designing, building, and deploying sophisticated models that solve complex business problems. You aren't just an expert in XGBoost or Transformers; you are an expert in building the <strong>pipelines</strong> that make these models reliable, scalable, and impactful.</p> <h3>WHAT YOU'LL DO<br><em><sup>Essential Job Duties & Functions</sup></em></h3> <ul> <li><strong>End-to-End Model Development:</strong> Design and implement the full ML lifecycle—from exploratory data analysis (EDA) and feature engineering to model selection, tuning, and validation.</li> <li><strong>GCP Architecture:</strong> Leverage the full Google Cloud AI suite (Vertex AI, BigQuery ML, Dataflow, and Pub/Sub) to build robust, cloud-native ML solutions.</li> <li><strong>MLOps & Engineering:</strong> Implement CI/CD for machine learning (CT - Continuous Training) to ensure models remain performant in production environments.</li> <li><strong>Strategic Leadership:</strong> Partner with stakeholders to translate ambiguous business challenges into technical roadmaps. Mentor junior scientists and advocate for best practices in code quality and experiment tracking