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# Machine Learning Engineer - Satellite Capacity Optimization & Planning

- **Company:** Viasat, Inc.
- **Location:** Carlsbad, CA, United States
- **Experience:** Expert
- **Salary:** $140,500.0 - $221,500.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Airflow, Amazon Web Services, BigQuery, Cloud Engineering, Data Presentation, Linear Programming, Machine Learning, Tensorflow, Standard Sql, Reinforcement Learning, Cloud Platform System, Pytorch, Orbital Mechanics, Optimization Algorithms, Data Analytics, Machine Learning Operations, Restful APIs
- **Published:** August 16, 2026
- **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/17964692?backUrl=%2Fcareer%2F17964692%2FMachine-Learning-Engineer-Satellite-Capacity-Optimization-Planning-California-Carlsbad

## About the Role

7+ years in ML/optimization roles

 - Strong background in optimization techniques (linear programming, constraint satisfaction, etc.)

 - Experience building production ML systems in cloud environments (AWS/GCP)

 - Experience with ML frameworks (TensorFlow, PyTorch, or equivalent)

 - Skilled at building geospatial visualizations and telling data-driven stories

 - Cloud-native containerized application development experience

 - Proficient in SQL

 - Comfortable building and maintaining RESTful APIs

 - Ability to travel up to 10%
What will help you on the job

 - Experience in satellite communications domain - link budgets, orbital mechanics

 - Production reinforcement learning systems experience

 - Airflow, Athena, BigQuery

 - Experience with ECS, Batch, or similar orchestration tools
Salary range

## Description

You will be a hands-on ML engineer building platforms and tooling to optimize supply allocation across our global satellite fleet to meet customer demand, and provide business stakeholders with planning insights.
The day-to-day

 - Develop models, optimizations, and tools for dynamic supply-demand optimization scenarios

 - Contribute to geospatial visualizations and data-driven storytelling for planning insights

 - Build and maintain production ML systems in cloud-native, containerized environments

 - Collaborate with SMEs and stakeholders to understand requirements and validate optimization approaches

 - Implement and iterate on demand/supply demand/supply modeling strategy and validate feasibility of optimization approaches
 - Build and maintain APIs that expose ML capabilities to downstream consumers
What you'll need


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