Cresta is on a mission to turn every customer conversation into a competitive advantage by unlocking the true potential of the contact center. They are seeking a Senior Machine Learning Engineer to help build the next generation of AI-powered voice systems, focusing on improving how AI interacts in live customer conversations.
Responsibilities:
- Design, train, evaluate, and deploy machine learning systems that power real-time voice experiences, including ASR, speech understanding, turn detection, text to speech, speech to speech, classification, entity extraction, summarization, and structured insight generation
- Improve the quality of voice AI systems through error analysis, data curation, metric design, benchmarking, and iterative model improvement, with a strong focus on real-world performance
- Build evaluation frameworks for complex voice and agentic systems, measuring metrics such as accuracy, robustness, latency, faithfulness, naturalness, professionalism, task completion, and cost
- Diagnose and mitigate failure modes across the voice stack, including transcription errors, hallucinations, retrieval failures, tool misuse, prompt brittleness, context drift, and multi-step reasoning breakdowns
- Design and optimize low-latency ML workflows for live conversations, balancing model quality with system responsiveness, scalability, and reliability
- Partner with platform and backend engineers to productionize real-time inference, streaming pipelines, quality monitoring, and continuous model iteration
- Collaborate cross-functionally with product, design, frontend, and backend teams to integrate voice intelligence seamlessly into Cresta’s platform
- Establish best practices for offline evaluation, online experimentation, model validation, observability, and ongoing quality monitoring in production
- Mentor engineers, contribute to technical strategy, and help shape the roadmap for Cresta’s voice AI systems
Requirements:
- Bachelor's degree in Computer Science, Mathematics, Machine Learning, AI, or a related field; Master's or Ph.D. preferred
- 5+ years of experience building, evaluating, and deploying machine learning systems in production
- Strong background in one or more of the following: speech recognition, speech processing, NLP, generative AI, or conversational AI
- Deep experience with model evaluation, benchmarking, error analysis, and quality improvement for production ML systems
- Strong expertise with modern ML frameworks and tooling such as PyTorch, TensorFlow, and Hugging Face
- Solid understanding of transformer-based models, embeddings, retrieval systems, and large-scale training or inference workflows
- Experience designing and deploying real-time ML systems with strong requirements around latency, scalability, and reliability
- Experience building data pipelines and tooling for experimentation, measurement, and large-scale quality analysis
- Ability to work across research and engineering boundaries and translate promising ideas into production-grade systems
- Strong communication and technical leadership skills, with the ability to influence cross-functional decisions and raise the engineering bar
- Hands-on experience with ASR quality metrics such as WER and task-level evaluation methodologies
- Experience with RAG systems, agentic workflows, multi-step reasoning systems, or LLM-as-a-judge evaluation methods
- Familiarity with streaming inference, real-time voice pipelines, or media systems
- Experience working closely with infrastructure or platform teams on production ML deployment, observability, and reliability
- Experience in contact center AI, conversational intelligence, or enterprise voice products