Platform Engineer Jobs
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HarmonEyes is the world's only open, AI-powered eye-tracking platform that identifies and predicts a person's cognitive, emotional, and physical state based on eye movements alone. Compatible with any camera-based device, HarmonEyes provides a one-stop shop to analyze eye-tracking data, develop models, and deploy solutions to applications at scale with the Theiaâ„¢ SDK. Backed by 60+ years of eye-tracking experience and born from the largest validated eye-tracking database (14 million unique records), HarmonEyes is used by the world's leading organizations in technology, aviation/automotive, healthcare, and elite performance in military and sports.
Job Description
Job Description
As a Platform Engineer, you'll build and own the software that takes our ML models from research to production: the Theia SDK that runs real-time inference at the edge, the APIs and services our customers and partners integrate with, and the cloud infrastructure behind our data and model pipelines. You'll work closely with our ML engineers and researchers, so you'll need to understand how models are trained, evaluated, and deployed, but your core focus is building reliable, well-designed systems around them.
What You'll Do
- SDK Development: Design, build, and maintain the Theia SDK in Python and C++, delivering real-time eye-tracking inference across desktop, mobile, embedded, and XR platforms. Own packaging, performance, versioning, and the developer experience.
- API & Backend Development: Design and implement APIs and backend services for data ingestion, model serving, licensing, and customer integrations, with a focus on clean interfaces, reliability, and security.
- Cloud Engineering: Build and operate infrastructure on AWS, including containerized services on Kubernetes, infrastructure-as-code, CI/CD, and monitoring.
- Full Stack: Build internal tools, dashboards, and customer-facing web interfaces that make our data and models accessible.
- Data Science Engineering: Build and scale the pipelines that process millions of eye-tracking records for training, evaluation, and analytics. Clean, transform, validate, and analyze large tabular datasets, and build the tooling that lets our ML team explore and work with data efficiently.
- ML Productionization: Partner with ML engineers to deploy, optimize, and monitor models in production and at the edge, including model conversion, latency and memory optimization, and inference pipelines.
Qualifications
Qualifications
Required
- 2–4 years of professional software engineering experience building production systems
- Strong Python skills, including packaging and distributing libraries
- Working familiarity with C++ (reading, modifying, and building C++ code in a cross-platform codebase)
- Experience designing and building APIs (REST, gRPC, or similar) and backend services
- Hands-on experience with AWS, containers, and CI/CD
- Experience working with large tabular datasets in pandas (data cleaning, transformation, aggregation, and performance at scale)
- Working familiarity with machine learning: you understand the model lifecycle and have helped deploy or integrate ML models in a product
- Strong communication skills and comfort working across engineering and research teams
Nice to Have
- Experience building and shipping SDKs or libraries used by external developers
- SQL and database engineering (schema design, query optimization, PostgreSQL or similar)
- Kubernetes and infrastructure-as-code (Terraform or similar)
- Frontend experience (React or similar)
- Edge or on-device inference (ONNX Runtime, TensorRT, TFLite, Core ML, or similar)
- Python compilation or distribution tooling (Nuitka, Cython, pybind11, or similar)
- Exposure to time-series, sensor, or signal-processing data
- Interest in VR/AR, eye tracking, or human-computer interaction
- 1 year experience in a research setting (developing or working with ML research domains)
Additional Information
Why Join Us
- Remote role with room to grow into automation, tooling, and AI-engineering work—not a pure manual-QA seat
- Direct exposure to a novel technical stack: real-time eye-tracking, ML pipelines, SDKs, and VR/AR integrations
- Tight feedback loop with senior engineering and leadership—the work you ship is felt across the company
How to Apply
This position reports into the engineering team. We're looking for someone who pairs solid QA fundamentals with curiosity for automation and AI-assisted workflows.
With your submission please attach:
- Your resume
- GitHub profile, portfolio, or links to relevant work (test suites, scripts, automations welcome)
- A short note on a bug you're proud of finding—or an automation/script that saved you or your team meaningful time
Platform Engineer Jobs by Experience Level
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Who's Hiring
- Google80

- Meta53

- JPMorganChase46

- Capital One37

- Booz Allen Hamilton37

Top Industries Hiring
- Technology & Software46
- Science & Research9
- Electronics & Hardware7
- Investment & Asset Management7
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What Employers Look For
The qualifications that appear most often in platform engineer jobs.
- Hands-on experience with Kubernetes, Docker, and container orchestration at scale
- Proficiency in infrastructure-as-code tools such as Terraform, Pulumi, or Ansible
- Experience designing and maintaining CI/CD pipelines using tools like Jenkins, GitHub Actions, or ArgoCD
- Strong knowledge of cloud platforms including AWS, Google Cloud Platform, or Azure
- Scripting or programming ability in Python, Go, Bash, or a comparable language
- Bachelor's degree in computer science, software engineering, or a related technical field
Tips for Your Platform Engineer Job Search
Tailor your resume to the stack
Platform engineer job descriptions vary sharply by stack. Rewrite your skills section for each application to mirror the exact tools listed, whether that's Kubernetes, Terraform, or Pulumi, so automated screening doesn't filter you out before a human sees your resume.
Document your reliability metrics concretely
Hiring managers for platform roles want to see outcomes, not duties. Quantify the uptime improvements, deployment frequency gains, or incident reduction your work delivered, even if the numbers came from a small-team environment or a side project.
Apply early to roles that fit
Migrate Mate lists platform engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Target companies by their infrastructure maturity
A seed-stage startup and a Fortune 500 enterprise need very different platform engineers. Read engineering blogs or release notes before applying so you can speak to their current tooling challenges, not a generic pitch, in your cover letter and interviews.
Prepare for system design in infrastructure context
Platform engineer interviews routinely include system design questions scoped to internal developer platforms, CI/CD pipelines, or multi-region architectures. Practice talking through trade-offs between self-hosted and managed services, not just application-layer design patterns.
Negotiate scope, not just compensation
In platform roles, the ownership boundary matters as much as the offer. During negotiation, clarify which systems you own end-to-end and whether on-call rotations are compensated separately, because those factors directly affect workload and long-term job satisfaction.
Platform Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most platform engineers?
The most active employers for platform engineers right now are Google, Meta, and JPMorganChase, and the most openings are in California, Texas, and New York, based on current listings on Migrate Mate as of November 2026. Demand is strongest at companies running large-scale cloud infrastructure or actively modernizing legacy systems.
How many platform engineer jobs are remote?
About 87% of platform engineer openings are fully remote or hybrid as of November 2026, making it one of the more remote-accessible engineering disciplines. Roles focused on cloud infrastructure management and internal developer platform tooling tend to be the most likely to offer fully distributed arrangements, while on-site is more common when physical data center access is required.
How do you become a platform engineer?
Most platform engineers start in software development, systems administration, or DevOps roles and build toward the discipline by deepening expertise in container orchestration, infrastructure-as-code, and CI/CD systems. Getting hands-on with Kubernetes and Terraform through personal projects or open-source contributions, then pursuing a cloud certification from a major provider, accelerates the transition significantly.
Can you get a platform engineer job with little experience?
Entry-level platform engineer roles do exist, but they typically expect familiarity with at least one cloud provider and basic scripting ability. Building a public GitHub portfolio that shows working CI/CD pipelines or containerized deployments, even from personal or academic projects, demonstrates practical competence when professional experience is limited. Internships in DevOps or cloud engineering roles are a reliable entry path.
What does the platform engineer interview process look like?
Platform engineer interviews typically include a recruiter screen, a technical phone interview covering infrastructure concepts, and a multi-stage loop with system design exercises scoped to internal developer platforms or cloud architecture. Many employers also include a practical component where you walk through a real or simulated infrastructure problem, explaining trade-offs in tooling choices, reliability design, and operational overhead out loud.
Where can I find and apply to platform engineer jobs?
You can find and apply to platform engineer jobs on Migrate Mate, which lists current openings from across the United States. Search for roles that match your stack and experience level, then apply directly to each listing that fits.
See All 2,293+ Platform Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
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