StratumAI - Forward Deployed Machine Learning Engineer (San Francisco) Job at Recruiting From Scratch, San Francisco, CA

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  • Recruiting From Scratch
  • San Francisco, CA

Job Description

Who is Recruiting from Scratch :

Recruiting from Scratch is a talent firm that focuses on placing the best candidate for our clients.

Forward Deployed Machine Learning Engineer

Location: Remote (US or Canada)
Company Stage: Seed-funded, backed by top-tier investors
Office Type: Remote-first
Salary: Competitive, with equity options

Company Description

Our 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 accuracyreducing waste, cutting costs, and maximizing profitability for mining operations. Supported by leading investors (including a prominent ex-OpenAI leader), theyre scaling their impact with a small, high-performance team.

What You Will Do

As a Forward Deployed ML Engineer , youll be the bridge between advanced AI research and real-world industrial applications. Youll:

  • Deploy custom deep learning models (PyTorch) to optimize mineral discovery and extraction for client sites.

  • Build robust data pipelines for noisy, unstructured mining data (geospatial, temporal, sensor data).

  • Design evaluation frameworks to measure model performance against industry benchmarks (e.g., block model accuracy).

  • Collaborate with geologists and engineers to 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.

Ideal Candidate Background

  • 2+ years of industry experience building/training custom neural networks (PyTorch strongly preferred).

  • Strong Python skills and experience with spatial/temporal data (e.g., geospatial, sensor, or time-series data).

  • Ability to communicate complex ML concepts to non-technical stakeholders (e.g., visualizations, reports).

  • Self-driven problem-solver who thrives in ambiguityyoull own projects end-to-end.

Preferred (Not Required)

  • Exposure to mining, geology, or resource modeling (huge plus, but well train you!).

  • Experience combating data drift/bias in production models.

  • Publications or open-source contributions in ML/geospatial domains.

Compensation & Benefits

  • 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.

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Job Tags

Full time, Work at office, Remote work,

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