QA Automation Engineer

20 godzin temu

Gdansk Metropolitan Area, Polska Luxoft Poland Pełny etat


Join us in Luxoft

Flexible working hours

Private Medical & Dental care & Life Insurance

Paid Referrals

MyBenefit program (sports card, well-being program etc.)

Internal Mobility program - possibility of rotation between projects, locations, accounts

LuxTalent platform (webinars, training, courses)


Project Description

Luxoft, in partnership with AMD, is seeking skilled QA Automation Engineers to join a team dedicated to validating next-generation visual computing technologies at scale. This group builds automated systems that verify visual outputs - images, videos, and real-time game scenes - across a wide range of GPU hardware and rendering pipelines.

As part of the Software QA Test Automation organization, you will design and evolve tooling that performs pixel-accurate and perceptual-based comparisons, automate visual regression workflows, and integrate these systems deeply into CI. You will develop and maintain frameworks for large-scale dataset inspection, automated artifact analysis, and visual quality benchmarking.

In this role, you will collaborate closely with Graphics, ML, and Rendering teams to ensure that cutting-edge GPU features meet the highest quality bar. You will evaluate emerging technologies, prototype validation strategies, and remove barriers to large-scale automated testing. Senior engineers will additionally partner with Dev, QA, and Program Management across new initiatives to identify automation opportunities and drive end-to-end quality improvements.

This position is ideal for engineers passionate about computer graphics, visual fidelity, and automation at scale - and who want hands-on access to state-of-the-art hardware, often before it reaches the market.


Responsibilities

  • Implement automated validation pipelines for image/video datasets (format checks, variance checks, content classification).

  • Develop visual regression tooling (pixel-compare, perceptual metrics, temporal consistency checks).

  • Build and maintain visualization dashboards and utilities to accelerate inspection and debugging.

  • Create automation to classify, cluster, and tag dataset content (including leveraging pretrained models where useful).

  • Integrate automated checks into CI/CD so regressions are detected early and reproducibly.

  • Produce reproducible scripts and tooling to capture model snapshots and run benchmark comparisons.

  • Collaborate with research/production to codify evaluation criteria and acceptance thresholds.


Skills

What is relevant to have

  • Strong programming skills (Python or similar), test automation, and scripting.

  • Experience processing and analyzing image/video datasets (frame extraction, codecs, metadata).

  • Familiarity with visual comparison techniques (SSIM, LPIPS, perceptual metrics) and how to implement them robustly.

  • Experience with CI systems (Jenkins, GitHub Actions, GitLab CI) and automating pipeline steps.

  • Good debugging skills and ability to make tooling resilient and maintainable.

What is nice to have

  • Experience with state-of-the-art ML models for media understanding (e.g., CLIP) and related open-source toolkits (Voxel51, FiftyOne, etc.).

  • Exposure to games or graphics pipelines.

  • Familiarity with benchmarking methodologies for AI, vision, or rendering applications.


Languages

English: C1 Advanced


Seniority

Regular


Work mode

hybrid in Gdansk

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