Lead AI/ML Engineer

ASAPP • Mountain View, CA

9d • Hybrid

About The Position

At ASAPP, our mission is simple: deliver the best AI-powered customer experience—faster than anyone else. To achieve that, we’re guided by principles that shape how we think, build, and execute. We value customer obsession, purposeful speed, ownership, and a relentless focus on outcomes. ASAPP’s AI Engineering team is seeking an enterprising, talented and curious machine learning engineer.

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

Requirements

• 6+ years of experience in Machine Learning or AI systems, with hands-on experience in LLMs, speech, or conversational AI systems
• Proficiency on Python and ML frameworks like PyTorch or TensorFlow
• Proven experience leading complex, cross-functional AI initiatives
• Experience building or integrating speech-to-text and text-to-speech systems
• Deep understanding of latency-sensitive system design and distributed architectures
• Strong proficiency in Python and ML frameworks such as PyTorch or TensorFlow
• Strong experience integrating foundational models into production applications
• 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

Nice To Haves

• Experience with speech model fine-tuning or 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

Responsibilities

• Lead the design and implementation of scalable ML/AI systems, with a focus on large language models, vector databases, and retrieval-based architectures
• 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

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) along with sick leave, bereavement and jury duty

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level