Senior Machine Learning Engineer – Automatic Speech Recognition (ASR)

About This Opportunity

We are representing a confidential conversational AI organization in their search for a Senior Machine Learning Engineer specializing in Automatic Speech Recognition. Our client is building next-generation AI-powered voice systems for enterprise contact centers, working at the cutting edge of speech, language, and real-time production systems.

In this role, you will develop and improve machine learning systems that power voice experiences end-to-end, including automatic speech recognition, turn detection, language understanding, retrieval-augmented workflows, quality measurement, text-to-speech, and production optimization. You'll partner closely with applied researchers, product managers, designers, and platform engineers to ensure model and system improvements translate into measurable customer and business impact.

This position is ideal for someone excited by both model quality and production reality: designing rigorous evaluation frameworks, analyzing failure modes, improving latency and robustness, and shipping systems that perform reliably at scale in real-time voice environments.

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 voice AI systems quality 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 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 the 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 voice AI systems

What We're Looking For

Required Qualifications:

• Bachelor's degree in Computer Science, Mathematics, Machine Learning, AI, or 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: 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 ability to influence cross-functional decisions

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

How We Work with You

When you apply through Get A Job.ai, our talent team will review your profile and conduct an initial screening to understand your background and career goals. If there's a strong match, we will submit your candidacy to our client for consideration. Please do not attempt to contact the client directly, as all communication should flow through our recruiting process to ensure the best outcome for your application.

Pay

This is a full-time position located in the United States with remote work options. Compensation details will be discussed during the screening process based on your experience and qualifications.

Equal Employment Opportunity: Get A Job.ai is committed to providing equal employment opportunities to all qualified individuals regardless of race, color, religion, sex, gender identity, sexual orientation, national origin, age, disability, or veteran status.