About the job
The Opportunity
Are you passionate about leading innovative projects that harness AI technology to enhance the value of meetings and conversations? Join our dynamic AI team at Otter.ai, where you will collaborate with seasoned scientists and engineers to advance our machine learning capabilities. As a Senior Machine Learning Engineer, you will leverage your robust software engineering expertise to scale and optimize our ML systems, transforming pioneering research into production-ready features that drive our summarization and conversational intelligence offerings.
Your Impact
- Design, build, and advance expansive Speech Recognition, Natural Language Processing, and Large Language Model systems that underpin essential product experiences, including chat and speech understanding across millions of interactions.
- Lead the architecture and development of training, fine-tuning, post-training, and inference methodologies for large-scale language and speech models utilizing PyTorch and/or JAX, making informed trade-offs among quality, latency, cost, and reliability.
- Enhance model architectures, loss functions, decoding methods, and training strategies for speech and language models, guided by both research insights and practical constraints.
- Oversee the complete ML system lifecycle, from research prototyping to production deployment, including monitoring, iteration, and ongoing maintenance.
- Collaborate closely with product and infrastructure teams to translate groundbreaking research into scalable, production-grade systems that yield significant user and business impact.
- Drive enhancements in model performance, reliability, observability, and operational excellence using real-world conversational data at scale.
- Establish technical direction and best practices for ML infrastructure, data pipelines, evaluation frameworks, and deployment processes in a cloud environment.
- Identify and resolve complex challenges in model behavior, data quality, scaling, and system interactions, often preemptively addressing issues before they affect users.
- Mentor and uplift fellow engineers, shaping team standards, reviewing designs, and fostering a culture of high-quality technical decision-making and execution.
- Influence applied research and technical strategies by pinpointing promising speech and multimodal modeling techniques, and driving their validation and adoption.

