ML Infrastructure Engineer (AI)

TL;DR

ML Infrastructure Engineer (AI): Designing and building scalable evaluation infrastructure for automated translation quality measurement with an accent on ML pipelines and production-grade systems. Focus on driving consistency in quality metrics across dubbing and localization products while partnering with R&D to iterate on evaluation methodology.

Location: Must be based in the UK, Germany, Switzerland, or Ireland (remote or in-office), with potential support for other European locations subject to compliance.

Salary: From €120,000 base + stock options.

Company

Synthesia is a leading AI video platform for business, pioneering advancements in Generative AI with a mission to enhance visual communication and enterprise skill development.

What you will do

• Design and build scalable evaluation infrastructure for automated translation quality measurement.
• Own the rollout of evaluation infrastructure across localization, dubbing, and other product teams.
• Drive consistency and automation in quality measurement across the entire pipeline.
• Partner with the R&D team to align evaluation infrastructure with real product and user quality signals.
• Maintain and iterate on evaluation systems as the product and pipeline evolve.
• Collaborate cross-functionally to ensure systems meet diverse product requirements.

Requirements

• Must be based in the UK, Germany, Switzerland, or Ireland (or other European locations subject to compliance).
• Strong ML infrastructure engineering background.
• Hands-on experience designing and scaling ML evaluation or quality measurement systems in production.
• Solid understanding of ML pipelines and model evaluation methodologies.
• Strong backend engineering fundamentals for shipping production systems.
• Experience working cross-functionally across multiple teams.

Nice to have

• Experience with LLMs applied to quality scoring or translation evaluation.
• Background in async or batch processing pipelines.
• Prior work in localization, dubbing, or media processing tooling.
• Familiarity with NLP, translation quality metrics, or speech/audio evaluation.

Culture & Benefits

• Full-time employment with stock option plan.
• 25 days of leave plus local holidays.
• Focus on building and shipping with minimal distractions.
• Work with a world-class team of AI researchers and engineers.
• Commitment to AI ethics, safety, and security.

Hiring process

• Technical recruiter call (30-40min).
• Engineering manager interview (45min).
• Live coding collaboration exercise (90min).
• System design discussion (60min).
• Leadership interview (45min).