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Coordinator Software Localization Engineer Jobs (NOW HIRING)

Italian-English Language Lead

Seattle, WA · On-site

$18.75 - $25.25/hr

... localization PMs, localization vendors and quality assurance engineers to drive linguistic ... language software localization and editing experience. • Excellent interpersonal and ...

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Coordinator Software Localization Engineer information

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$67K

$129.7K

$224K

How much do coordinator software localization engineer jobs pay per year?

As of Jul 8, 2026, the average yearly pay for coordinator software localization engineer in the United States is $129,678.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,000.00 and $141,000.00 per year, depending on experience, location, and employer.
What cities are hiring for Coordinator Software Localization Engineer jobs? Cities with the most Coordinator Software Localization Engineer job openings:
What are the most commonly searched types of Software Localization Engineer jobs? The most popular types of Software Localization Engineer jobs are:
What states have the most Coordinator Software Localization Engineer jobs? States with the most job openings for Coordinator Software Localization Engineer jobs include:
Localization Algorithm Engineer

Localization Algorithm Engineer

OtterBase

Detroit, MI • On-site

Other

Re-posted 10 days ago


Job description

Job Description Description: This role focuses on developing and optimizing localization algorithms using probabilistic methods and multi-sensor fusion to improve positioning accuracy. You will prototype, simulate, and refine solutions into production-ready code while collaborating across software, hardware, and systems teams in a fast-paced R&D environment. Responsibilities/skills: Develop and refine PC-based localization algorithms using particle filters and other probabilistic techniques.

Implement sensor fusion strategies that integrate data from IMUs, wireless signals, and other external sources to enhance position accuracy. Design simulations to test and validate your algorithms under diverse real-world conditions (e.g., multipath, noise, varying environments). Leverage Python, C++, C#, or MATLAB to prototype and optimize algorithms before porting them to production software

Conduct thorough performance evaluations of localization algorithms, identifying bottlenecks and implementing data-driven optimizations. Collaborate with embedded, FPGA, and RF teams to improve the performance of the location tracking system. Stay current with the latest academic and industry research in probabilistic localization, sensor fusion, and state estimation.

Rapidly prototype novel concepts, iterating on algorithm design to reach production-level stability and robustness. Work cross-functionally with software, hardware, and systems engineers to integrate localization algorithms into larger systems. Contribute to code reviews, knowledge sharing, and team brainstorming sessions to maintain a high level of technical excellence.

Qualifications: Solid background in state estimation, probability theory, and advanced filtering techniques (particle filters, Kalman filters, etc.). Proficiency in at least one programming language (Python, C#, C++, MATLAB) used for developing and evaluating algorithms in a PC-based environment. Solid understanding of DSP algorithms and IQ radio processing

Experience translating theoretical models into efficient, production-ready code, with an emphasis on real-time or near-real-time performance. Familiarity with sensor data processing (IMU, etc.) and a keen interest in multi-sensor fusion methods. Adept at using data analytics and simulations to diagnose issues, validate assumptions, and refine algorithmic approaches

Passionate about exploring new ideas, adapting cutting-edge research, and creatively applying them to solve challenging localization problems. Enjoys working as part of a multi-disciplinary R&D team, bridging gaps between software, hardware, and system-level designs. Thrives on tackling open-ended challenges, taking ownership of tasks, and seeking continuous learning opportunities.