2

Full Time Mining Dispatch Jobs (NOW HIRING)

... in mining environments. You'll work on path planning, multi-vehicle coordination, and dispatch ... Benefits Summary (USA Full-Time Exempt Employees): * Medical, Dental, Vision, Disability, and Life ...

Driller

Elko, NV · On-site

S. The mine is located in White Pine County, one of the best mining jurisdictions in the world ... GPS/dispatch navigation system(s). • Connects drill pipe sections using hand tools and power ...

Showing results 41-60

Full Time Mining Dispatch information

See salary details

$30K

$62.9K

$103.5K

How much do full time mining dispatch jobs pay per year?

As of Sep 10, 2026, the average yearly pay for full time mining dispatch in the United States is $62,888.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,000.00 and $71,500.00 per year, depending on experience, location, and employer.

What is the difference between Full Time Mining Dispatch vs Part Time Mining Dispatch?

AspectFull Time Mining DispatchPart Time Mining Dispatch
Work HoursTypically 40+ hours per weekLess than 30 hours per week
CertificationsRequired certifications often include dispatch and safety trainingMay require similar certifications but on a less intensive basis
Work EnvironmentOn-site at mining operations or centralized dispatch centersFlexible, may include remote or part-time on-site work
Employer UsageCommon in large mining companies for continuous operationsUsed by smaller operations or for supplemental staffing

Full Time Mining Dispatch involves working standard hours with comprehensive responsibilities for coordinating mining activities, while Part Time Mining Dispatch offers flexible hours with similar duties but on a reduced schedule. Both roles require relevant certifications and are essential for efficient mining operations, but differ mainly in hours and commitment level.

What cities are hiring for Full Time Mining Dispatch jobs?

Cities with the most Full Time Mining Dispatch job openings:

What are the most commonly searched types of Mining Dispatch jobs?

The most popular types of Mining Dispatch jobs are:

What are popular job titles related to Full Time Mining Dispatch jobs?

For Full Time Mining Dispatch jobs, the most frequently searched job titles are:

Infographic showing various Full Time Mining Dispatch job openings in the United States as of September 2026, with employment types broken down into 1% As Needed, 91% Full Time, 6% Part Time, and 2% Contract. Highlights an 99% Physical, and 1% Remote job distribution, with an average salary of $62,888 per year, or $30.2 per hour.

Senior Robotics Planning Engineer

San Francisco, CA

$176K - $240K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted 4 days ago


Key responsibilities

  • Develop high-level autonomy systems for fleet coordination of autonomous haul trucks in mining environments.

  • Design and implement motion planning algorithms, including path planning and trajectory optimization, for non-holonomic vehicles.

  • Create multi-agent coordination systems to prevent deadlocks and collisions, and develop fleet management algorithms for dynamic task assignment.


Job description

Who we are
Pronto AI is a global leader in commercializing autonomous vehicle (AV) technology, deploying Autonomous Haulage Systems (AHS) that automate operations in mines, quarries, and construction sites worldwide. While much of the industry remains in R&D, we deliver real, production-ready autonomy that is already operating in the field.
We are on a mission to make mining operations safer, smarter, and more efficient through cutting-edge technology, and we are building toward becoming the world's first profitable AV technology company.

What you'll do

We're looking for a Robotics Planning Engineer to develop the high-level autonomy systems that coordinate fleets of autonomous haul trucks in mining environments. You'll work on path planning, multi-vehicle coordination, and dispatch systems that operate at the site level - deciding where trucks go, when they go, and how they interact with each other.

  • Motion planning - A robust stack, from path planning to trajectory optimization, to generate smooth and safe trajectories for 200+ ton trucks to follow.
  • Coordination planning - Systems to simultaneously coordinate the motion of multiple vehicles with intersecting trajectories to avoid collision and maximize throughput.
  • Fleet planning - Algorithms that dynamically translate the site-wide state, like loading and dumping locations, to actively managed assignments for each truck.
  • Design and implement motion planning algorithms for non-holonomic vehicles
  • Develop multi-agent coordination systems that prevent deadlocks and collisions
  • Build simulation and visualization tools for validating planning algorithms
  • Optimize planning algorithms for real-time performance in production environments
  • Collaborate with controls engineers to ensure planned paths are executable
  • Debug fleet-level issues using logged data and replay tools
  • Travel note: This role requires periodic travel to customer sites (up to 5%)
  • Schedule note: Some schedule flexibility may be required during deployments

What we're looking for

  • BS/MS/PhD in Robotics, Computer Science, or related field required
  • 3+ years of professional (non-internship) software development experience
  • Strong foundation in motion planning algorithms
  • Experience with computational geometry (collision detection, polygon operations)
  • Proficiency in Python and NumPy for numerical computing
  • Understanding of vehicle kinematics and nonholonomic constraints
  • Ability to analyze algorithm complexity and optimize for real-time performance

Preferred Qualifications

  • Experience with multi-agent coordination or scheduling algorithms
  • Familiarity with Dubins/Reeds-Shepp curves for non-holonomic planning
  • Background in trajectory optimization (DCBF, MPC-based planners)
  • Experience with graph algorithms (Dijkstra, heuristic search)
  • Knowledge of GEOS, Shapely or other computational geometry libraries
  • Experience with fleet management or dispatch systems
  • Familiarity with Redis, ZeroMQ, or similar infrastructure
  • Familiarity with modern ML techniques for planning problems

Technical Environment

  • Languages: Python (primary), C++ (performance-critical modules)
  • Libraries: NumPy, Shapely, Numba, SciPy
  • Testing: Simulation replay, config-driven scenario testing

Why join us 

  • Work on real, production-deployed autonomy.
  • Build technology that directly improves safety, efficiency, and productivity.
  • Tackle complex challenges in demanding, real-world environments.
  • Be part of a fast-moving team with high ownership and impact.
  • See your work deployed and making a difference in the field.
  • Collaborate closely with experienced engineers and industry operators.

What else you need to know 

This role is based in our San Francisco office location. As a company driven by innovation and continuous change, close collaboration is essential. We're constantly reimagining our industry, creating new products, and refining our processes, and we do our best work together. That's why all of our office-based teams work onsite, five days a week. 

The base salary range for this role is $176,000 - $240,000 per year.

Actual compensation will be determined on an individual basis and may vary depending on experience, skills, and qualifications.

Base salary is just one part of your total rewards package. You may also be eligible for equity awards.

Benefits Summary (USA Full-Time Exempt Employees):

  • Medical, Dental, Vision, Disability, and Life Insurance
  • Flexible Spending Account / Health Savings Account Options
  • 401(k)
  • Equity
  • Sick Time, Unlimited Flexible Time Off, and Paid Holidays
  • Paid Parental Leave 
  • Pre-Tax Commuter Benefit Plan
  • Team lunch in our SoMa office every Tuesday and Thursday

Benefits are subject to change at the company's discretion.
Pronto accepts applications on an ongoing basis.

Ready to join us as we serve those who serve others? 

#LI-Onsite