Senior Machine Learning Engineer

About the role

NiCE is looking for a Senior Machine Learning Engineer to join NiCE Labs Research (NLR), a team dedicated to model expertise and agent architecture for the Cognigy platform. The role involves owning the evaluation and optimization of speech-oriented AI models, covering real-time transcription and speech-to-speech systems across dozens of languages.

Responsibilities

• Design and maintain a speech-oriented test suite covering quality, cost, and latency across dozens of languages.
• Monitor the industry for new state-of-the-art transcription and speech-to-speech models to evaluate.
• Design and evaluate techniques to optimize speech model usage for operational deployment.
• Produce clear, quantitative evaluation reports and model recommendations for technical and non-technical stakeholders.
• Contribute to the broader model evaluation framework maintained by the NLR team.
• Stay informed of advances in speech AI, including transcription, text-to-speech, and speech-to-speech technologies.

Requirements

• MS in computer science, electrical engineering, computational linguistics, or a related field with a focus on speech or audio processing.
• Three or more years of hands-on experience with speech AI systems, including ASR, TTS, or speech-to-speech models.
• Experience designing evaluation methodologies or test suites for AI systems.
• Strong quantitative and analytical skills, with experience producing rigorous benchmark results.
• LoRA/PEFT for speech models, inference optimization (quantization, SGLang/vLLM serving for audio, distillation), experience with at least one open-source TTS family.
• Proficiency in Python and familiarity with speech processing libraries and tools.
• Experience with cloud-based infrastructure (AWS, Azure, or GCP).

Qualifications

• Ability to develop and maintain good working relationships with cross-functional teams.
• Ability to clearly communicate and present to internal and external stakeholders.

Skills

• Experience evaluating speech models across multiple languages.
• Familiarity with multi-cloud deployment across AWS, Azure, and Google Cloud.
• Experience with model optimization techniques for speech systems, such as latency reduction or cost optimization.
• Exposure to contact center or conversational AI platforms.
• Experience working on international, globe-spanning teams.

Benefits

Join an ever-growing, market disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment!

NiCE-FLEX: 2 days working from the office and 3 days of remote work, each week.

Pay

Competitive compensation package.

Schedule

Hybrid model: 2 days working from the office and 3 days of remote work, each week.