Data Scientist III - AI & Machine Learning

ABOUT onX 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. 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. 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. 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. 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. ABOUT THIS OPPORTUNITY 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 pipelines that make these models reliable, scalable, and impactful. WHAT YOU'LL DO Essential Job Duties Functions End-to-End Model Development: Design and implement the full ML lifecycle—from exploratory data analysis (EDA) and feature engineering to model selection, tuning, and validation. GCP Architecture: Leverage the full Google Cloud AI suite (Vertex AI, BigQuery ML, Dataflow, and Pub/Sub) to build robust, cloud-native ML solutions. MLOps Engineering: Implement CI/CD for machine learning (CT - Continuous Training) to ensure models remain performant in production environments. Strategic Leadership: 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. Look for opportunities to embed AI as a repeatable co-pilot in daily workflows by integrating experimentation into real work, and continuously refining its use with sound judgment and validation. WHAT YOU’LL BRING 5+ years in a professional Data Science role with a track record of deploying models at scale. Proficiency in Vertex AI, BigQuery, Cloud Storage, and Looker. Experience with Kubeflow is a major plus. Expert-level Python (pandas, scikit-learn, PyTorch/TensorFlow), Spark, and advanced SQL. Deep understanding of statistics and ML theory (e.g., Gradient Descent, Bias-Variance tradeoff, Bayesian inference). Experience with ETL/ELT processes, specifically using dbt. A strong curiosity for exploring new technologies, including AI A shared passion for and ability to demonstrate onX’s Company Values. Permanent US work authorization is a condition of employment with onX. Our Tech Stack Data Warehouse: BigQuery Orchestration: Airflow (Cloud Composer) Modeling: Vertex AI Pipelines, JupyterLab Deployment: Docker, GKE (Google Kubernetes Engine) Pro Tip for the Candidate: We value "clean code" as much as "smart math." If you treat your notebooks like production scripts and your Git history is a work of art, you’ll fit right in. What Sets You Apart The "Product" Mindset: You understand that a model with 99% accuracy is useless if it costs more to run than the value it creates. Infrastructure as Code: You are comfortable with Terraform or similar tools to manage your cloud resources. ... (truncated, view full listing at source)