• Free
  • Published date: May 22, 2019
    • Texas, United States

At M1neral, we deliver opportunity to investors in mineral rights on both a local and an institutional level. Our core platform and big data solutions deliver best-in-class insights and analytics on the mineral markets and are overlaid on our geospatial applications. Our platform is built to support large-scale data sources and incorporates both structured and unstructured sources. Our data ingestion pipelines, processing power, and geospatial displays allow investors to target, research, and track the mineral marketplace anywhere in the USA.

Job Description
As a Machine Learning Engineer, you will be building out the backbone of M1nerals services. You will utilize cutting-edge artificial intelligence technologies to map and valuate mineral investments. You will lead engineering efforts on new features and enhancements, which will include upfront planning, thorough testing, and release to production. This will require close communication with product, design, and other engineers on the team to coordinate deliverables and navigate changes in priorities. Our team is committed to constantly improving, and as a senior team member, you will have the opportunity to grow individually, and be expected to contribute to our engineering practices and culture.

What We Offer
Unlimited PTO
Equity Incentive Plan
Flexible Work Hours / Work From Home Flexibility
Company Sponsored Benefits
Maternity & Paternity Leave
Paid Holidays
Volunteer Time Off
Job Training & Professional Development
Stocked Kitchen
$1000 Vacation Stipend (vested)
Job Requirements
Advanced degree (Masters or PhD) in computer science, engineering, or equivalent, with a focus on machine learning
2-3 years of professional data science experience
Strong familiarity with Python, R, Scala, or equivalent
Strong theoretical knowledge, including mathematical foundations, of modern machine learning systems and techniques
Practical experience implementing and expanding on a variety of machine learning models
Strong statistical background and ability
Experience working with both real-time data and large offline datasets
Experience implementing, testing, and deploying code to a production environment
Ability to work effectively in a team environment
Ability and eagerness to learn new technologies quickly
On-site preferred, but remote work acceptable.
Interview process will consist of a phone interview, a technical coding challenge, and an in-person interview with the founding team.
Interested? We thought so. Contact us to join the revolution.

Email our team at

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