Lead AI/ML Engineer

About the role

This role is part of ASAPP's mission to deliver the best AI-powered customer experience faster than anyone else. It involves building real-time conversational AI systems, integrating speech-to-text and text-to-speech systems, and optimizing low-latency inference workflows for multimodal applications.

Responsibilities

• Build real-time conversational AI systems, including voice interfaces powered by speech-to-text, text-to-speech, and streaming inference pipelines
• Design and optimize low-latency inference workflows for multimodal applications involving text, speech, and real-time interactions
• Integrate and apply foundation models from major providers (OpenAI, AWS Bedrock, Anthropic, etc.) for prototyping and production use cases
• Adapt, evaluate, and optimize LLMs for domain-specific enterprise applications
• Build and maintain infrastructure for experimentation, deployment, and monitoring of AI models in production
• Improve model performance and inference workflows with attention to latency, cost, and reliability
• Provide technical leadership within the team, mentoring engineers and promoting best practices in ML engineering
• Partner with product and cross-functional stakeholders to translate requirements into scalable ML solutions
• Contribute to the evolution of internal standards for experimentation, evaluation, and deployment

Requirements

• 6+ years of experience in Machine Learning or AI systems, with hands-on experience in LLMs, speech, or conversational AI systems
• Strong experience integrating speech-to-text and text-to-speech systems
• Proficiency on Python and ML frameworks like PyTorch or TensorFlow
• Proven experience leading complex, cross-functional AI initiatives
• Deep understanding of latency-sensitive system design and distributed architectures
• Strong proficiency in Python and ML frameworks such as PyTorch or TensorFlow
• Understanding of RAG pipelines, prompt engineering, and vector search
• Experience deploying and scaling AI systems using AWS (required), Docker, Kubernetes, and CI/CD practices
• Strong communication skills with the ability to align engineering, product, and executive stakeholders
• Comfortable operating in fast-paced environments and driving clarity in ambiguous problem spaces

Qualifications

• Experience with speech model fine-tuning and acoustic/language model optimization
• Hands-on experience with real-time or streaming audio systems (WebRTC, gRPC streaming, or similar architectures)
• Experience optimizing TTS prosody, pronunciation control, and voice customization
• Background in MLOps, experimentation platforms, or evaluation frameworks for speech and conversational systems
• Contributions to open-source AI or speech tooling
• Graduate degree (MS or PhD) in Computer Science, Machine Learning, Speech Processing, or related field

Skills

• Experience with speech model fine-tuning and acoustic/language model optimization
• Hands-on experience with real-time or streaming audio systems (WebRTC, gRPC streaming, or similar architectures)
• Experience optimizing TTS prosody, pronunciation control, and voice customization
• Background in MLOps, experimentation platforms, or evaluation frameworks for speech and conversational systems
• Contributions to open-source AI or speech tooling

Benefits

• Competitive compensation with stock options
• Comprehensive medical, vision, and dental insurance
• 401k matching
• Fitness and wellness stipend
• Mental well-being benefits
• Professional learning and development stipend
• Parental leave, including adoptive and foster parents
• 3 weeks paid time off (increases with tenure) and unlimited sick leave
• $170,000 - $190,000 a year compensation package also includes a performance bonus on top of the listed salary range
• Separately, we also offer a compelling equity grant comprised of stock options