Lead AI/ML Engineer, ASAPP

• 6+ years of experience in Machine Learning or AI systems, with hands-on experience in LLMs, speech, or conversational AI systems
• Experience building on integrating speech-to-text and text-to-speech systems
• Strong experience integrating voice models into production applications
• 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

Desirable

• We are seeking a highly experienced Lead AI/ML Engineer to join our Core GenerativeAgent team
• You will play a pivotal role in designing, building, and deploying cutting-edge AI systems that power mission-critical enterprise applications
• This role is ideal for an individual who thrives in ambiguity, is deeply technical, and has a strong product sense paired with deep expertise in foundational models and enterprise AI systems
• You will lead the design and delivery of end-to-end voice AI solutions, combining large language models with speech technologies such as speech-to-text, text-to-speech, and real-time streaming audio pipelines
• This role requires a hands-on technical leader who can architect low-latency, highly reliable conversational voice systems and guide a team through ambiguity toward production excellence
• We are looking for someone who understands the unique constraints of voice experiences, latency, turn-taking, interruption handling, streaming inference, and audio quality, and can translate these into scalable, enterprise-grade systems
• This is a hybrid role with weekly in-person responsibilities. We have offices in New York City and Mountain View, CA
• 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