Senior Machine Learning Engineer
Lead projects building and deploying large-scale ASR, NLP, and LLM systems for meeting intelligence. Requires 5+ years building production ML systems with PyTorch/JAX and experience with speech/language models.
About the job
Your Impact
- Architect, build, and evolve large-scale SID / ASR / NLP / LLM systems that power mission-critical product experiences including summarization, chat, and speech understanding across millions of conversations.
- Lead the design and implementation of training, fine-tuning, post-training, and inference strategies for large language and speech models using PyTorch and/or JAX, making principled trade-offs across quality, latency, cost, and reliability.
- Design and improve model architectures, loss functions, decoding strategies, and training techniques for speech and language models, informed by both research and production constraints.
- Own end-to-end ML system lifecycles, from research prototyping through production deployment, monitoring, iteration, and long-term maintenance.
- Partner deeply with product, and infrastructure teams to develop and translate cutting-edge research into scalable, production-grade systems that deliver measurable user and business impact.
- Drive system-level improvements in model performance, robustness, observability, and operational excellence using real-world conversational data at scale.
- Set technical direction and best practices for ML infrastructure, data pipelines, evaluation frameworks, and deployment workflows in a cloud environment.
- Identify and resolve complex, ambiguous problems in model behavior, data quality, scaling, and system interactions, often before they surface as user-visible issues.
- Mentor and elevate other engineers, influencing team standards, reviewing designs, and contributing to a culture of strong technical decision-making and execution.
We're Looking for Someone Who
- Holds a Bachelor’s or Master’s degree in Computer Science or a related field with 5+ years of relevant industry experience; PhD is preferred.
- Has deep, hands-on experience building and fine-tuning large language or foundation models, with production experience in ASR, TTS, multimodal, or modern LLM/NLP systems, and a strong understanding of model failure modes and trade-offs.
- Demonstrates strong command of modern ML research, with the ability to critically evaluate new papers and drive innovation by identifying what is production-worthy versus experimental.
- Has extensive experience deploying, scaling, monitoring, and operating ML systems in production across training, inference, and serving infrastructure, including model versioning, rollback strategies, and performance regression detection while balancing cost, latency, and reliability constraints.
- Is comfortable working with large-scale speech and conversational datasets, including data preprocessing, augmentation, quality analysis, and labeling strategies to support model training and evaluation.
- Is highly effective at cross-functional collaboration, working end-to-end with product, infra, research, and data teams to deliver outcomes, not just models.
- Can lead technical projects independently, driving clarity in ambiguous problem spaces and making sound architectural decisions.
- Has experience with or strong interest in agentic systems, tool-use frameworks, or multi-model orchestration.
- Has experience with personalization, recommendation systems, or user modeling is a plus.
Skills
PyTorch, JAX, Asr, NLP, LLMs, Sid, Tts, Machine Learning, Model Training, Fine-Tuning, Inference, Speech Models, Data Preprocessing, Model Evaluation
Similar jobs
ML Engineering jobs
Baselayer
San Francisco, CA
Senior AI Engineer responsible for production LLM agents that enrich business identity data through web discovery, verification, classification, and risk scoring. The role requires strong asynchronous Python, agent and evaluation expertise, browser automation, and experience operating AI systems in production.
Otter
Mountain View, CA
Leads the development and production deployment of large-scale ASR and TTS systems for conversational intelligence products. The role requires 5+ years of industry experience, deep speech-model expertise, and strong software engineering and ML operations capabilities.
Ambience Healthcare
San Francisco, CA
Build and improve production AI systems for clinical products, owning evaluations, model behavior, agentic workflows, data flywheels, deployment, and observability. The role requires 5+ years of production ML or applied AI experience, strong Python and modern ML framework skills, and hands-on debugging expertise.
Dialpad
United States
Leads development of speech models, decoders, and low-latency inference systems for next-generation voice agents. Requires 5+ years in speech ML or related audio AI, strong Python and PyTorch experience, and the ability to guide technical direction and mentor engineers.
Ontario, Canada
Design, build, and deploy production ML systems for recommendations, search, ranking, and advertising at internet scale. Own the full ML lifecycle from modeling to monitoring with strong cross-functional collaboration.