Job Location : all cities,CA, USA
Location: Remote (US or Canada)Company Stage:Seed-funded, backed by top-tier investorsOffice Type:Remote-firstSalary:Competitive, with equity options
Company DescriptionOur client is a cutting-edge AI company revolutionizing the mining and resource extraction industry. Their proprietary machine learning models analyze geospatial and operational data to predict mineral distributions with unprecedented accuracy—reducing waste, cutting costs, and maximizing profitability for mining operations. Supported by leading investors (including a prominent ex-OpenAI leader), they're scaling their impact with a small, high-performance team.
What You Will DoAs aForward Deployed ML Engineer, you'll be the bridge between advanced AI research and real-world industrial applications. You'll:
Deploy custom deep learning models(PyTorch) to optimize mineral discovery and extraction for client sites.
Build robust data pipelinesfor noisy, unstructured mining data (geospatial, temporal, sensor data).
Design evaluation frameworksto measure model performance against industry benchmarks (e.g., block model accuracy).
Collaborate with geologists and engineersto translate model insights into actionable strategies.
Contribute to foundational research(40% of time) to improve core algorithms across all deployments.
Solve high-stakes problems—your work directly impacts multi-million-dollar mining decisions.
2+ years ofindustry experiencebuilding/training custom neural networks (PyTorch strongly preferred).
Strong Python skills and experience withspatial/temporal data(e.g., geospatial, sensor, or time-series data).
Ability tocommunicate complex ML conceptsto non-technical stakeholders (e.g., visualizations, reports).
Self-driven problem-solver who thrives in ambiguity—you'll own projects end-to-end.
Exposure tomining, geology, or resource modeling(huge plus, but we'll train you!).
Experience combatingdata drift/biasin production models.
Publications or open-source contributions in ML/geospatial domains.
Salary:Competitive, commensurate with experience.
Equity:Generous stock options in a high-growth startup.
Flexibility:Fully remote with async-first culture.
Impact:Your models will shape the future of sustainable resource extraction.
Perks: Health benefits, learning stipend, and team offsites.