Summer Intern Data Engineer/Software Engineer

Confirmed live in the last 24 hours

Echodyne Corp

Kirkland, WA

On-site

Posted April 8, 2026

Job Description

Radar Reinvented.

Echodyne offers the world’s first compact solid-state true beam-steering radar for a wide range of industries and applications. Our high-performance radars work in all weather and are designed for autonomous vehicles, uncrewed aircraft & drones, and security of borders, critical infrastructure, and smart cities. The company combines the patented technology of metamaterials with powerful software to create a radar sensor with unprecedented performance at commercial price points. Echodyne offers its radars to companies working in Automotive, Transportation, Critical Infrastructure Protection, Border Security, Smart Cities, Uncrewed Aircraft Systems (UAS), and Airspace Management including Urban Air Mobility (UTM).

Echodyne is seeking a Summer Intern Data Engineer/Software Engineer to join our fast-growing team.

ROLE OVERVIEW

We are looking for a Summer Intern – Data/Software Engineering to support our data engineering and analytics team in the development of an automated Radar-to-GPS Track Alignment and Target Data Ingestion Tool. This role focuses on building a Python-based application that aligns GPS-equipped target telemetry with radar track data, automates time synchronization, and enables interactive visualization and analyst-in-the-loop refinement. This is an exciting opportunity for students interested in software development, radar data processing, scientific computing, or applied algorithms to gain hands-on experience while contributing to a high-impact internal R&D tool. The Mentor for this internship is the Sr Data Engineer.

RESPONSIBILITIES

Develop a Python-based alignment engine to automatically synchronize and minimize positional error between radar track latitude/longitude data and GPS target telemetry.
Implement algorithms for time offset estimation and optimization (e.g., cross-correlation, non-linear least squares, dynamic time warping, or state-space estimation approaches).
Support classification-informed track selection to prioritize candidate radar tracks matching operator-specified target types.
Document algorithms, workflows, and best practices to ensure repeatability and usability by radar analysts.
Develop AI-assisted workflows to detect and parse new GPS file formats and convert them into a canonical structure for reuse.
Prototype an interactive user interface (Panel/Param with Bokeh or Plotly) for visualizing trajectory alignment, adjusting time offsets, and reviewing residual errors.

ESSENTIAL DELIVERABLES

A functional alignment library capable of estimating time offsets and minimizing positional error between radar and GPS trajectories.
Documentation describing supported alignment algorithms, configuration options, error metrics, and recommended analyst workflows.
A final presentation summarizing methodology, validation results, and recommendations for future enhancements.

AS TIME ALLOWS DELIVERABLES

A reusable ingestion and converter framework for target GPS file formats.
An interactive Python application supporting trajectory visualization, alignment execution, and manual refinement.
Develop libraries to further improve radar/target alignment by rotational error estimation and applying correctional rotations to improve alignments.

QUALIFICATIONS

Currently pursuing a degree in Computer Science, Engineering, Applied Mathematics, Data Science, or a related field, with preference for students in their junior year or above.
Strong

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