United States (Remote)•US (Remote)
Remote
Senior
Full Time
2 days ago
💰$205,000 - $270,000
machine learningvoice AIreal-time systemssenior
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.
What You'll Do
- •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.
Nice to Have
- •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.
Benefits
- •Comprehensive medical, dental, and vision coverage with plans to fit you and your family
- •Flexible PTO to take the time you need, when you need it
- •Paid parental leave for all new parents welcoming a new child
- •Retirement savings plan to help you plan for the future
- •Remote work setup budget to help you create a productive home office
- •Monthly wellness and communication stipend to keep you connected and balanced
- •In-office meal program and commuter benefits provided for onsite employees
About Cresta
Cresta uses artificial intelligence to assist sales and service agents in the quality of customer service.
Palo Alto, CA, US
250 - 500
AI & Machine Learning