StratumAI - Forward Deployed Machine Learning Engineer

Recruiting From Scratch; California; Remote; USD 90,000 - 150,000; Full time

Job summary

An innovative AI firm is seeking a Forward Deployed Machine Learning Engineer to bridge advanced AI research with real-world applications in the mining industry. This role involves deploying custom deep learning models, building data pipelines, and collaborating with geologists to translate insights into actionable strategies. As part of a high-performance team, you'll contribute to foundational research and solve high-stakes problems that directly impact multi-million-dollar decisions. If you're a self-driven problem-solver with a passion for machine learning and sustainability, this opportunity is perfect for you.

Benefits

Health benefits

Learning stipend

Team offsites

Generous stock options

Qualifications

• 2+ years of experience building/training custom neural networks, preferably with PyTorch.
• Strong Python skills and experience with spatial/temporal data.

Responsibilities

• Deploy custom deep learning models to optimize mineral discovery and extraction.
• Build robust data pipelines for noisy, unstructured mining data.

Skills

Deep Learning

Python

Machine Learning

Data Analysis

Problem Solving

Communication

Education

Bachelor's Degree in Computer Science or related field

Tools

PyTorch

Data Pipelines

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.