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At NiCE, we don’t limit our challenges. We challenge our limits. Always. We’re ambitious. We’re game changers. And we play to win. We set the highest standards and execute beyond them. And if you’re like us, we can offer you the ultimate career opportunity that will light a fire within you. So, what's the role all about? 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. As Senior Machine Learning Engineer, you will own the evaluation and optimization of speech-oriented AI models — covering real-time transcription and speech-to-speech systems across dozens of languages. This role is primarily concerned with rigorous measurement: designing test suites, running comparative evaluations, and producing actionable recommendations on model selection and configuration. The Senior Machine Learning Engineer monitors the rapidly evolving speech AI landscape to identify state-of-the-art transcription and speech-to-speech models for evaluation. You will design and maintain a speech-oriented test suite that covers quality, cost, and latency, and develop techniques to optimize model usage for operational deployment. This role requires deep expertise in speech AI systems, strong quantitative skills, and the discipline to produce reliable, reproducible evaluation results. How will you make an impact? 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. Have you got what it takes? 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 GPU cost modeling Proficiency in Python and familiarity with speech processing libraries and tools. Experience with cloud-based infrastructure (AWS, Azure, or GCP). Ability to develop and maintain good working relationships with cross-functional teams. Ability to clearly communicate and present to internal and external stakeholders. You will have an advantage if you have: 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. What’s in it for you? 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! As the market leader, every day at NiCE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NICEr! Enjoy NiCE-FLEX! At NiCE, we work according to the NiCE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere. Requisition ID: 11422 Reporting into: Director, Engineering, AI Research, NiCE Labs Role Type: Individual Contributor About NiCE NICE Ltd. (NASDAQ: NICE) software products are used by 25,000+ global businesses, including 85 of the Fortune 100 corporations, to deliver extraordinary customer experiences, fight financial crime and ensure public safety. Every day, NiCE software manages more than 120 million customer interactions and monitors 3+ billion financial transactions. Known as an innovation powerhouse that excels in AI, cloud and digital, NiCE is consistently recognized as the market leader in its domains, with over 8,500 employees across 30+ countries. NiCE is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, age, sex, marital status, ancestry, neurotype, physical or mental disability, veteran status, gender identity, sexual orientation or any other category protected by law.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.