Senior Software Engineer, AI Data

About AssemblyAI

AssemblyAI builds the best-in-class Speech AI models powering the next generation of voice applications. Our models serve 600M+ inference calls monthly, process 1M+ hours of audio daily, and power 2 billion+ end-user experiences—from voice agents and meeting assistants to contact centers and medical scribes. Companies like Zoom, Granola, Fireflies, Cluely, and Calabrio rely on AssemblyAI to ship production-ready voice AI.

We're at an inflection point in Speech AI. We released Universal-Streaming in mid-2025, and it has quickly earned its place as the model offering the best accuracy-latency-cost tradeoff on the market. Our research team drives these advances and ships with relentless velocity. Since releasing Universal-Streaming, we've already launched keyterms prompting feature and multilingual support—with more significant improvements on the roadmap.

We've raised $115M+ from Accel, Insight Partners, Y Combinator's AI Fund, Patrick and John Collison, Nat Friedman, and Daniel Gross. We're a remote team building one of the next great AI companies—and we're looking for people who will shape its future.

About the Role

We're seeking an exceptional Senior Software Engineer to join our AI Data team. This role is focused on building robust, scalable systems that power our AI data platform. You’ll work on high-impact projects that directly influence our ability to train and evaluate models at scale, with a strong emphasis on software engineering excellence, system reliability, and code quality.

As a Senior Engineer, you'll drive technical execution within your team, taking ownership of significant features and components. You should be passionate about writing clean, maintainable code, implementing comprehensive testing strategies, and continuously improving engineering practices. This role requires close collaboration with researchers, platform engineers, and other stakeholders. You'll need to balance technical excellence with pragmatic delivery in a fast-paced startup environment.

What You’ll Do

Architect Next-Gen AI Data Infrastructure

Design scalable, future-proof data platforms optimized for AI research workloads

Build efficient self-serve data processing pipelines leveraging GCP's advanced services

Implement cost-effective storage and monitoring solutions for ML at scale

Create flexible training resource management with intelligent queuing

Optimize resource allocation for maximum training efficiency

Participate in on-call rotation to ensure system reliability

Advance Technical Excellence

Lead adoption of cutting-edge ML tools and frameworks, continuously evaluating and integrating best-in-class solutions

Streamline existing workflows while introducing new tooling that further reduces complexity

Enhance our tooling and documentation to accelerate team velocity and maintain our competitive edge

Implement guardrails for cost, quality, and performance

Identify and eliminate technical bottlenecks in the data processing and training pipelines

What You’ll Need

5+ years of professional software engineering experience

Strong proficiency in Python and SQL with demonstrated ability to write production-quality code

Solid understanding of software engineering fundamentals

• Data structures and algorithms
• System design and architectural patterns
• Testing strategies (unit, integration, end-to-end)
• Code review practices and technical collaboration

Experience with

• RESTful APIs and distributed systems concepts
• Containerization (Docker) and basic cloud infrastructure

Track record of delivering high-quality software in a team environment

Ability to thrive in a startup environment with changing priorities and rapid iteration

Preferred

• Experience with GCP services (BigQuery, GCS, Cloud Run, GKE)
• Familiarity with distributed processing frameworks (Apache Beam, PySpark)
• Experience with workflow orchestration tools (Airflow, Prefect, Dagster)
• Understanding of ML/AI infrastructure and data pipelines
• Experience wit