Senior Technical Program Manager – AI Tooling & Systems

🔥 0 minutes ago

🇺🇸 United States – Remote

💵 $152k - $190k / year

⏰ Full Time

🟠 Senior

👮‍♀️ Software Engineering Manager

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Deepgram

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2015

🤖 Artificial Intelligence

☁️ SaaS

🔌 API

💰 $47M Series B on 2022-11

Artificial Intelligence • SaaS • API

Deepgram is a leading voice AI company that provides powerful APIs for speech-to-text, text-to-speech, and language understanding applications. Their platform enables developers to build sophisticated voice AI solutions for use cases such as contact centers, medical transcription, conversational AI, and more. Known for unmatched accuracy, speed, and cost-effectiveness, Deepgram's technology is trusted by top enterprises and startups worldwide. By offering real-time and highly accurate transcription capabilities, Deepgram helps businesses gain insights from voice data, making it an essential tool for transforming voice interactions.

📋 Description

• Own end-to-end delivery of AI infrastructure programs—from model training pipelines and experiment tracking to inference serving and production monitoring • Define technical architecture, integration patterns, and rollout strategies for new ML systems and tooling (e.g., vector databases, model servers, evaluation frameworks, prompt engineering platforms) • Serve as connective tissue between ML research, ML engineering, product, and data teams to align on ML system requirements, capability roadmaps, and deployment timelines • Drive cost and latency optimization for real-time inference workloads at scale • Build lightweight internal tools and processes to accelerate ML iteration cycles (experiment tracking, model versioning, A/B testing infrastructure) • Identify and resolve technical bottlenecks in training pipelines, serving infrastructure, and model evaluation workflows • Work closely with ML practitioners to translate research breakthroughs into scalable, observable systems

🎯 Requirements

• 5+ years of program management or technical leadership in ML infrastructure, ML platforms, or AI tooling (or equivalent) • Strong technical acumen in ML systems—ideally hands-on experience as an ML engineer, systems engineer, or ML infrastructure engineer • Experience coordinating cross-functional ML programs (e.g., model training → evaluation → serving → monitoring) • Proven ability to translate ML/research requirements into robust, scalable infrastructure • Comfortable working in ambiguity and helping teams navigate complex technical tradeoffs (e.g., accuracy vs. latency vs. cost) • Excellent communication with both technical and non-technical stakeholders • Familiarity with high-growth or startup environments • It Would Be Great If You Had • Hands-on experience with model serving frameworks (vLLM, TensorRT, TorchServe, or similar) • Experience optimizing LLM or speech/audio model inference (quantization, distillation, KV-cache optimization, batching strategies) • Familiarity with ML experiment tracking and versioning tools (MLflow, Weights & Biases, DVC, or similar) • Background in feature stores, vector databases, or real-time ML systems • Knowledge of cost optimization for GPU/ML workloads on cloud and on-premise infrastructure • Experience with multi-region model serving or edge deployment • Hands-on with relevant frameworks (PyTorch, CUDA, Hugging Face, etc.) or cloud platforms (AWS SageMaker, GCP Vertex AI, Azure ML)

🏖️ Benefits

• Offers Equity • Offers Bonus • 10% Annual Bonus