Senior Machine Learning Engineer

Senior Machine Learning Engineer (Voice AI)

Join Cresta to build and improve machine learning systems for real-time voice experiences. You’ll work across speech and language capabilities and help take models and pipelines from design to production.

Role overview

• Develop end-to-end ML systems that power voice interactions in real time
• Collaborate with product, design, frontend, and backend teams to deliver high-quality voice AI
• Drive continuous improvements based on real-world performance and quality metrics

Responsibilities

• Design, train, evaluate, and deploy ML systems for 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 voice AI quality via:
  • Error analysis, data curation
  • Metric design, benchmarking
  • Iterative model improvements with emphasis on production performance
• Partner with platform/backend teams to productionize:
  • Real-time inference and streaming pipelines
  • Quality monitoring and continuous model iteration

Requirements

• 5+ years building, evaluating, and deploying production ML systems
• Strong technical leadership and communication; ability to influence cross-functional decisions
• Experience building data pipelines and tooling for experimentation, measurement, and large-scale quality analysis
• Expertise with modern ML frameworks and tooling: PyTorch, TensorFlow, Hugging Face
• Deep experience with model evaluation, benchmarking, error analysis, and production quality improvement
• Ability to translate research ideas into production-grade systems
• Background in one or more of: speech recognition, speech processing, NLP, generative AI, conversational AI
• Experience with real-time ML systems with requirements for latency, scalability, and reliability
• Solid understanding of transformer-based models, embeddings, retrieval systems, and large-scale training/inference workflows
• Hands-on with ASR quality metrics such as WER and task-level evaluation
• Familiarity with streaming inference/real-time voice pipelines or media systems

Nice to have

• Experience with RAG systems, agentic workflows, multi-step reasoning, or LLM-as-a-judge evaluation
• Experience in contact center AI, conversational intelligence, or enterprise voice products
• Experience working with infrastructure/platform teams on production ML deployment, observability, and reliability

Remote

• Full remote