QA Team Lead

Luxoft; Województwo pomorskie; On-site; PLN 100,000 - 120,000; Full time

Job summary

A leading technology services company in Poland is seeking a proactive QA Team Lead to oversee quality assurance for visual media. This role requires strong programming skills in Python and experience in building QA infrastructure for validating image and video datasets. The ideal candidate will guide a team, implement inspection and validation techniques, and contribute to continuous integration efforts. Competitive compensation and opportunities for mentoring in a dynamic environment offered.

Qualifications

• Experience leading QA teams for visual media.
• Direct experience with ML models for media understanding.
• Familiarity with continuous integration workflows.

Responsibilities

• Own the QA strategy for visual media quality.
• Lead a QA team on data inspection and validation.
• Build tooling for visual inspection of datasets.

Skills

Leadership in QA

Python programming

Automated validation

Benchmarking methodologies

Continuous integration workflows

Tools

CLIP

Voxel51

FiftyOne

Job description

Project description

We are seeking a talented and proactive QA Team Lead with strong programming and tool building skills. The ideal candidate will set up robust validation and inspection systems (both automated and manual) to ensure the highest quality in our data generation and application outputs. This role sits at the intersection of engineering and visual validation, requiring independence, initiative, and deep technical know how in building QA infrastructure and tooling. The Team Lead is expected to be hands on in Python, guide the team in tool development, and evaluate modern ML based media understanding tools such as CLIP and Voxel51.

Responsibilities

• Own the overall QA strategy for visual media, combining automated and manual approaches to ensure the quality and variance of data sets (generated or existing) through inspection and validation techniques. Define validation workflows and acceptance criteria for image and video datasets, game scenes, and application outputs. Lead a small team of QA engineers (manual, automation, data quality) by planning, prioritizing, and distributing work, monitoring progress, and removing blockers. Build and maintain, together with the team, tooling for fast and effective visual inspection of image and video datasets, including utilities that support pixel based analysis and visual regression. Oversee the development of internal applications and utilities in Python to automate classification, clustering, and validation of dataset content, plus visualization tools that support efficient manual inspection. Coordinate the setup and evolution of continuous integration (CI) systems that automate regression testing (for example image comparison and visual regression checks) across graphical outputs and game scenes. Guide benchmarking efforts where, given a model snapshot, the team identifies and captures sequences showing problems and compares them with state of the art outputs. Stay updated with and evaluate open source options for dataset classification and visualization (for example CLIP, Voxel51, FiftyOne) and drive adoption of promising solutions in the workflow. Work closely with engineering, research, and production teams to embed quality check systems into applications and make manual and automated inspections more efficient. Mentor junior team members in both QA methodology and coding practices (Python or similar), and foster a self‑driven culture where engineers can set up pieces of infrastructure from scratch.

SKILLS

Must have

• Experience leading QA teams that build systems for visual media (games, graphics, rendering, computer vision). Background in benchmarking methodologies for AI, vision, or rendering applications. Direct experience with state‑of‑the‑art ML models for media understanding (for example CLIP) and open source toolkits such as Voxel51 or FiftyOne. Prior work with continuous integration workflows that validate outputs of graphical or global illumination techniques.

Nice to have

Exposure to leadership or mentorship