AI Research Engineer (Speech & Conversational AI)

About Diabolocom

Diabolocom enables organizations worldwide to build brand loyalty and drive sales growth through its cloud-based contact center platform. Our solution leverages AI-driven technologies to optimize customer experience across all communication channels.

About the role

At Diabolocom, we build AI systems that operate on real-world customer conversations across voice and text channels. We are looking for a Research Engineer to bridge the gap between cutting‑edge research and production‑grade telephony AI. You will be responsible for end‑to‑end contribution across our research roadmap, with a focus on building production‑ready systems for contact‑center voice and text channels.

What you will contribute to

• Production Speech AI: Building high-performance pipelines for ASR, TTS, and Speech-to-Speech (S2S) workflows.
• Agentic LLM Engineering: Implementing fine‑tuning, function/tool calling, and low‑latency inference for real‑time translation and agentic planning.
• Data‑Centric Research: Designing scalable pipelines for synthetic data generation and automated quality evaluation.

What we are looking for

• ML/DL foundations: Solid grounding in modern ML/DL, with experience training models at scale.
• Speech & Audio: Expertise in S2S systems (Moshi, Qwen3 Omni), ASR pipelines (Whisper, Qwen3), TTS, and signal processing fundamentals.
• Software Engineering: Solid Python skills, with a focus on clean, reproducible code, testing, and Git workflows.
• Research Edge: A background in navigating ambiguity, reading/implementing SOTA papers, and a track record of contribution (papers, blogs, or open source).

Valuable assets

• Experience with speaker/voice anonymization or privacy‑preserving techniques.
• Background in audio classification.
• Experience with real-time low-latency systems.
• Familiarity with cross‑lingual speech models or bidirectional LMs.

What we offer

• Research with grounded impact: Bridge theoretical breakthroughs and production problems, solving them at scale.
• Contribute to open‑source and in‑house products: Work alongside a team of researchers and engineers to build our products and publish SOTA research.