Deepgram
Applied ML Engineer
About this role
Deepgram is seeking an Applied ML Engineer to bridge research and production by owning the end-to-end pipeline that transforms speech AI models from experimental checkpoints into scaled, reliable services. You'll collaborate with research scientists to productionize models, build deployment infrastructure, and establish quality gates across a hybrid GPU and cloud environment.
What you'll do
- Own the research-to-production pipeline, converting research checkpoints into production-ready models with repeatable processes
- Partner with research scientists to translate experimental code into robust, reproducible training and evaluation workflows
- Build tooling and abstractions that streamline model movement through training, evaluation, packaging, and deployment
- Design and maintain model release gates with automated evaluation, regression detection, and performance checks
- Optimize models for production inference including batching, memory tuning, and latency optimization
- Instrument production behavior and establish feedback loops to inform future model iterations
What they're looking for
- ML productionization and deployment pipelines
- Python and ML frameworks (TensorFlow, PyTorch, or similar)
- Infrastructure and DevOps (GPU compute, cloud platforms, containerization)
- Model optimization and profiling for inference
- Benchmarking, testing, and quality assurance automation
- Systems engineering and performance tuning
- Scripting and tooling development
- Collaborative problem-solving with research teams
Benefits
- Remote work, USA-based
- Work on cutting-edge speech AI at billion-scale
- Hybrid infrastructure environment (custom GPU datacenters + cloud)
- Opportunity to define ML delivery practices
- AI-first culture with emphasis on innovation
- Series C-backed company with strong investor backing
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Deepgram
Deepgram builds voice AI and speech processing technology, offering platforms that power real-time speech recognition and audio intelligence across cloud, edge, and embedded environments. The company is hiring applied ML engineers, backend engineers, embedded AI engineers, and customer-facing roles (customer success and pre-sales engineers) to scale its AI infrastructure and drive enterprise adoption.
- Website
- deepgram.com
Likely interview questions
- Describe a time you took a research model or prototype and prepared it for production—what were the biggest bottlenecks?
- How do you approach optimizing a neural network for low-latency inference at scale?