Platform Engineer

RightEye

. Design, build, and maintain the Theia SDK in Python and C++ for real-time eye-tracking inference across desktop, mobile, embedded, and XR platforms .

Posted 11/2/2026full-timeRemote • Maryland • United StatesJuniorMid-LevelWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in Python and C++ for SDK development, with a strong focus on building APIs, managing AWS infrastructure, and optimizing machine learning models. Proficient in handling large datasets and enhancing developer experience through effective tooling and performance optimization.

Highest-signal resume keywords

Python ProgrammingC++ DevelopmentAWS Infrastructure ManagementAPI Design and DevelopmentMachine Learning Integration

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

PythonC++API DesignData CleaningData TransformationMachine LearningSDK DevelopmentSQLKubernetesCI/CD

Soft Skills

Strong Communication

Tools & Technologies

AWSKubernetesTerraformPandasReactONNX RuntimeTensorRTTFLiteCore MLNuitka

Industry Keywords

Eye TrackingReal-Time InferenceEmbedded SystemsXR PlatformsHuman-Computer Interaction

Tech Stack

Tools & technologies

AWSGRPCKubernetesPandasPostgresPythonReactSQLTerraformC++

About the role

Key responsibilities & impact

Design, build, and maintain the Theia SDK in Python and C++ for real-time eye-tracking inference across desktop, mobile, embedded, and XR platforms
Own SDK packaging, performance, versioning, and developer experience
Design and implement APIs and backend services for data ingestion, model serving, licensing, and customer integrations
Build and operate AWS infrastructure, including containerized services on Kubernetes, infrastructure-as-code, CI/CD, and monitoring
Build internal tools, dashboards, and customer-facing web interfaces
Build and scale pipelines processing millions of eye-tracking records for training, evaluation, and analytics
Clean, transform, validate, and analyze large tabular datasets
Build tooling enabling ML teams to explore and work with data efficiently
Partner with ML engineers to deploy, optimize, and monitor models in production and at the edge
Perform model conversion, latency and memory optimization, and inference pipeline development

Requirements

What you’ll need

2–4 years of professional software engineering experience building production systems
Strong Python skills, including packaging and distributing libraries
Working familiarity with C++, including reading, modifying, and building C++ code in a cross-platform codebase
Experience designing and building APIs such as REST or gRPC and backend services
Hands-on experience with AWS, containers, and CI/CD
Experience working with large tabular datasets in pandas, including data cleaning, transformation, aggregation, and performance at scale
Working familiarity with machine learning and understanding of the model lifecycle, including deploying or integrating ML models in a product
Strong communication skills and comfort working across engineering and research teams
1 year of experience in a research setting developing or working with ML research domains
Nice to have: experience building and shipping SDKs or libraries used by external developers
Nice to have: SQL and database engineering, including schema design, query optimization, and PostgreSQL or similar
Nice to have: Kubernetes and infrastructure-as-code such as Terraform
Nice to have: frontend experience such as React
Nice to have: edge or on-device inference technologies such as ONNX Runtime, TensorRT, TFLite, or Core ML
Nice to have: Python compilation or distribution tooling such as Nuitka, Cython, or pybind11
Nice to have: exposure to time-series, sensor, or signal-processing data
Nice to have: interest in VR/AR, eye tracking, or human-computer interaction

Benefits

Comp & perks

Remote role
Room to grow into automation, tooling, and AI-engineering work
Direct exposure to real-time eye-tracking, ML pipelines, SDKs, and VR/AR integrations
Tight feedback loop with senior engineering and leadership
Opportunity to work on software whose impact is felt across the company