QA Engineer — Hardware-Software Systems

Company: SwitchOn (Abee Research Pvt Ltd)
Location: Bengaluru (on-site, with occasional visits to customer factories)
About SwitchOn

SwitchOn is a Series A deep-tech startup eliminating defects in manufacturing with AI-powered vision inspection. Our systems run on factory lines at Unilever, ITC, P&G, Godrej, SKF, Bajaj, Brakes India and other leading manufacturers — inspecting products in real time, 24/7, where a missed defect can mean a recalled batch.

About the role
Our stack runs end to end: cameras and lighting on the line, edge hardware, firmware, ML inference, backend services, and a customer-facing dashboard. A bug anywhere in that chain shows up on a factory floor. We're looking for a QA engineer who can understand the whole system, build the automation that catches failures before our customers do, and still get hands-on to break things a script wouldn't think of.
You'll be our first dedicated QA hire — you'll shape how testing works here, not inherit a process.

What you'll do

• Learn the full hardware-to-dashboard stack and map where failures originate — camera drops, network flakiness, model drift, UI regressions, config errors.
• Build and own the test automation framework from the ground up: UI (dashboard), API (backend services), and integration tests across the edge-to-cloud pipeline.
• Wire automated suites into CI/CD (GitHub Actions) so every PR and release candidate runs regression automatically, with clear pass/fail gating.
• Set up hardware-in-the-loop test rigs — camera, lighting, edge device — so firmware and inference changes are validated against real captures, not just mocks.
• Build synthetic and recorded test datasets (image sets, sensor streams, edge-case product variants) that can be replayed to reproduce field failures deterministically.
• Simulate factory conditions — poor connectivity, power cycles, hardware faults — and verify the system degrades gracefully.
• Work with developers from spec stage to design test plans for new features, and reproduce and triage issues reported from the field.
• Create testing guidelines and release criteria the dev team follows, and own the go/no-go call on releases.
• Track and drive automation coverage, flaky-test rates, and time-to-detect regressions as team metrics.

What we're looking for

• 3+ years in test automation for hardware-software systems — IoT, robotics, industrial automation, med-tech or similar — with at least one framework you built or substantially owned.
• Strong Python; production experience with Pytest plus at least one of Playwright, Selenium or Cypress for UI, and requests/httpx or Postman/Newman for APIs.
• Experience integrating test suites into CI pipelines and keeping them fast and reliable at scale.
• Comfortable with Linux, Docker, shell scripting, and reading logs and code to isolate root cause.
• Understanding of test design for non-deterministic systems — you know how to test an ML model's output without asserting exact values.
• A customer-first instinct: you think in terms of what the plant operator sees at 2 a.m., not just whether the ticket passes.
• Clear written communication — bug reports and test docs that developers act on without a follow-up meeting.

Nice to have

• Experience testing computer-vision pipelines or validating ML models (accuracy regression, drift detection, golden datasets).
• Hardware-in-the-loop or embedded test experience (serial/CAN/GPIO automation, power-cycle rigs).
• Performance and load testing tools (Locust, k6) on real-time or streaming data.
• Familiarity with PLCs, OPC-UA or Modbus, or shop-floor environments.

Why join us

• Ownership from day one: define QA at a company where your work directly decides whether a production line ships good product.
• Deep-tech problems most QA roles never touch — hardware, ML and software failing in combination.
• Backed by Pi Ventures, Axilor, Chennai Angels and other leading deep-tech investors in India and Singapore.
• A clear path into a QA lead role as the team grows.