David AI
Software Engineer, Machine Learning Infrastructure
New
140000 –230000 USD / yearUSAMiddlepythoncloudgpumicroservicesapimonitoringlogging
Build and scale infrastructure for audio machine learning products including data pipelines, model training frameworks, and deployment systems.
Responsibilities
- Design and maintain data pipelines for processing massive audio datasets, ensuring terabytes of data are managed, versioned, and fed into model training efficiently.
- Develop frameworks for training audio models on compute clusters, managing cloud resources, optimizing GPU utilization, and improving experiment reproducibility.
- Create robust infrastructure for deploying ML models to production , including APIs, microservices, model serving frameworks, and real-time performance monitoring.
- Apply software engineering best practices with monitoring, logging, and alerting to guarantee high availability and fault-tolerant production workloads.
- Translate research prototypes into production pipelines , working with ML engineers and data teams to support efficient data labeling and preparation.
- Evaluate and integrate new MLOps technologies and optimization techniques to enhance infrastructure velocity and reliability.
Nice to have
- Experience with feature stores, experiment tracking (MLflow, Weights and Biases), or custom CI/CD pipelines.
- Familiarity with large-scale data ingestion and streaming systems (Spark, Kafka, Airflow).
- Proven ability to thrive in fast-moving startup environments.
Conditions
- Rapid career growth at one of the fastest growing Series A companies, within a new and booming industry.
- Competitive salary and equity package.
- Flexible PTO policy.
- Top-notch health, dental, and vision coverage with 100% company reimbursement for most plans.
- Paid lunch and dinner in the office, every day through DoorDash.
- 401k access.
Other
- At David AI, our engineers build the pipelines, platforms, and models that transform raw audio into high-signal data for leading AI labs and enterprises. We're a tight-knit team of product engineers, infrastructure specialists, and machine learning experts focused on building the world’s first audio data research company.
- We move fast, own our work end-to-end, and ship to production daily. Our team designs real-time pipelines handling terabytes of speech data and deploys cutting-edge generative audio models.
- As a Software Engineer, Machine Learning Infrastructure at David AI, you will build and scale the core infrastructure that powers our cutting-edge audio ML products. You’ll be leading the development of the systems that enable our researchers and engineers to train, deploy, and evaluate machine learning models efficiently.
- 5+ years of backend engineering with 2+ years ML infrastructure experience.
- Hands-on experience scaling cloud infrastructure and large-scale data processing pipelines for ML model training and evaluation.
- Proficient with Docker, Kubernetes, and CI/CD pipelines.
- Proven ML model deployment and lifecycle management in production.
- Strong system design skills optimizing for scale and performance.
- Proficient in Python with deep Kubernetes experience.
- Next.js, TypeScript, TailwindCSS, Node.js, tRPC, PostgreSQL, AWS, Trigger.dev , WebRTC, FFmpeg.