StratumAI - Forward Deployed Machine Learning Engineer

Recruiting From Scratch; San Francisco (CA); Remote; USD 120,000 - 160,000; Full time

Job summary

A leading AI company is seeking a Forward Deployed Machine Learning Engineer to bridge advanced AI research with real-world applications in the mining industry. You will deploy models, build data pipelines, and work directly with engineers and geologists to optimize mining operations. Ideal candidates have industry experience in neural networks and strong communication skills, with the flexibility to work remotely.

Benefits

Health benefits

Learning stipend

Team offsites

Qualifications

• 2+ years of industry experience building/training custom neural networks.
• Strong Python skills focused on spatial/temporal data.
• Ability to communicate complex ML concepts to non-technical stakeholders.

Responsibilities

• Deploy custom deep learning models (PyTorch) for optimizing mineral discovery/extraction.
• Build robust data pipelines for unstructured mining data.
• Collaborate with geologists to translate insights into actionable strategies.

Skills

Deep learning models

Python

Spatial/temporal data

Communication of ML concepts

Problem-solving

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 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 Do

As 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.

Ideal Candidate Background

• 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.

Preferred (Not Required)

• 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.

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.