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Salary: USD 183,000 - 298,000 / annual
Hubble Network is building a global Bluetooth network dedicated to machine-to-machine connectivity via satellite, positioning itself as the first modem-less, gateway-less, direct-to-satellite network from off-the-shelf Bluetooth Low Energy chips. The company targets logistics, AgTech, and maritime applications for asset tracking at scale, with a vision to become the first billion-endpoint-connected network.
As Principal Localization Engineer, you will lead the development of robust location computation systems leveraging Hubble's dual-stack BLE + satellite telemetry. This is a highly technical and strategic role focused on solving complex state estimation problems at scale. You will work cross-functionally with signal processing experts, firmware engineers, and data infrastructure teams to push the limits of what's possible in dynamic, global-scale environments. The role has high visibility and direct impact on core product performance and customer acquisition.
Key Responsibilities:
- Architect and implement cutting-edge location estimation algorithms based on BLE and satellite data, including Kalman filters, Extended Kalman Filters (EKF), and Particle Filters
- Optimize for computational efficiency, real-world performance, and cost—balancing precision with system constraints
- Build and deploy production-grade statistical and probabilistic models for state tracking and error correction
- Partner with Data Engineering to define data collection, structuring, and processing pipelines that support robust modeling
- Evaluate and iterate on models based on live system performance and simulation feedback
- Collaborate with cross-functional stakeholders, including embedded systems and backend infrastructure teams, to ensure end-to-end feasibility and integration
Requirements:
- 7+ years of hands-on, industry experience in applied state estimation, robotics, or signal processing roles
- Deep expertise in state estimation and sensor fusion, with practical implementation of Kalman, EKF, or Particle filtering techniques
- Strong understanding of geolocation systems, signal propagation models, and statistical inference under uncertainty
- Proven track record of bringing algorithms from prototype to production in real-world, resource-constrained systems
- Strong foundational SQL skills (AWS Redshift, AWS Athena, or Trino/PrestoSQL) to pull and validate analytical datasets
- Strong Python programming skills, with emphasis on numerical methods, simulation, and performance optimization
- Experience working closely with data engineering teams or building pipelines to support analytical model development
- Strong communication skills and ability to synthesize complex technical ideas for both technical and non-technical audiences
- U.S. citizen or lawful permanent resident (green card holder) as required by ITAR
Preferred Qualifications:
- Background in robotics localization, GN&C, autonomous systems perception, or RF geolocation
