AI/ML Platform Engineer

Role overview Own the machine learning systems behind conversational agents, from language models and speech recognition and synthesis to retrieval, grounding, and evaluation. The role combines applied research with production engineering: systems must respond quickly over voice channels while remaining predictable and auditable in regulated settings. You will also assess emerging models and techniques for their practical value.

Responsibilities - Design and operate the AI/ML stack, including language models, ASR, TTS, retrieval, and grounding components. - Build evaluation practices that measure quality and support reliable behavior in production. - Improve response latency for live voice interactions while preserving conversational quality. - Decide which behaviors should be handled by deterministic logic and which by language models. - Support auditability and predictable outcomes for applications in regulated sectors. - Track model releases and relevant research, then assess what should be integrated.

Requirements - Strong experience building or operating production machine learning systems. - Practical understanding of language models and speech technologies, including recognition and synthesis. - Ability to balance latency, quality, reliability, and auditability in system design. - Experience using AI tools in daily engineering work and reviewing their output. - English proficiency at approximately B2 level and Polish at approximately C1 level; other languages are welcome.

Nice to have - Work on low-latency voice systems, such as incremental dialogue handling or end-of-turn detection. - Experience with model fine-tuning, dialogue systems, or AI for regulated domains.

Benefits and work setup - Remote, hybrid, or office-based work, with flexible hours and a choice of B2B or employment contract. - Company-paid AI development tools and model access. - Direct ownership and close collaboration with engineering leadership and founders in a results-focused environment.