Deepgram

2 weeks ago

Senior Technical Program Manager (Engineering) - AI Tooling & Systems

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Own end-to-end delivery of AI infrastructure and tooling programs, from model training pipelines and experiment tracking to inference serving and production monitoring. Define technical architecture and rollout strategies for ML systems and tooling such as vector databases, model servers, and evaluation frameworks. Partner across ML research, engineering, product, and data to align roadmaps, unblock bottlenecks, and optimize real-time inference cost and latency.

Location: United States

Workplace: Remote

Employment Type: Full time

Job Function: Program & Project Management (PMO)

Seniority: Mid level

Key Responsibilities

•Own end-to-end delivery of AI infrastructure programs, including training pipelines, experiment tracking, inference serving, and production monitoring.
•Define technical architecture, integration patterns, and rollout strategies for new ML systems and tooling such as vector databases, model servers, and evaluation frameworks.
•Connect 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 internal tools and processes to accelerate ML iteration cycles and resolve technical bottlenecks across training, serving, and evaluation workflows.

Pay and Benefits

Salary: USD 152,000 - 190,000 annually

Equity and Bonus:Equity

Perks:Annual BonusEquity

Key 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 as an ML engineer, systems engineer, or ML infrastructure engineer.
•Experience coordinating cross-functional ML programs across training, evaluation, serving, and monitoring.
•Ability to translate ML/research requirements into robust, scalable infrastructure.
•Comfort working in ambiguity and communicating complex technical tradeoffs (accuracy vs. latency vs. cost).

Experience:5+ yearsML infrastructureML platformsAI toolingStartup environments

Skills:CommunicationCross-functional collaborationLeadershipProblem-solvingManaging ambiguity

Tech Stack:VLLMTensorRTTorchServeMLflowWeights & BiasesDVCVector databasesModel serversEvaluation frameworksPrompt engineering platformsA/B testingPyTorchCUDAHugging FaceAWS SageMakerGCP Vertex AIAzure MLExperiment trackingModel versioning

Company Brief

Deepgram

Deepgram builds a real-time Voice AI platform delivering speech-to-text, text-to-speech, and voice-agent APIs for developers and enterprises, focusing on low-latency, high-accuracy voice models and scalable deployment options.

Industry: API Platforms

Company Size: Medium (51 to 250 employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series C

Headquarters: San Francisco, United States

Founded: 2015

Glassdoor: 4.5

Website LinkedIn Glassdoor

Loading job details...

Preparing the role view and application actions.

Deepgram

2 weeks ago

Senior Technical Program Manager (Engineering) - AI Tooling & Systems

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Location: United States

Workplace: Remote

Employment Type: Full time

Job Function: Program & Project Management (PMO)

Seniority: Mid level

Key Responsibilities

•Own end-to-end delivery of AI infrastructure programs, including training pipelines, experiment tracking, inference serving, and production monitoring.
•Define technical architecture, integration patterns, and rollout strategies for new ML systems and tooling such as vector databases, model servers, and evaluation frameworks.
•Connect 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 internal tools and processes to accelerate ML iteration cycles and resolve technical bottlenecks across training, serving, and evaluation workflows.

Pay and Benefits

Salary: USD 152,000 - 190,000 annually

Equity and Bonus:Equity

Perks:Annual BonusEquity

Key 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 as an ML engineer, systems engineer, or ML infrastructure engineer.
•Experience coordinating cross-functional ML programs across training, evaluation, serving, and monitoring.
•Ability to translate ML/research requirements into robust, scalable infrastructure.
•Comfort working in ambiguity and communicating complex technical tradeoffs (accuracy vs. latency vs. cost).

Experience:5+ yearsML infrastructureML platformsAI toolingStartup environments

Skills:CommunicationCross-functional collaborationLeadershipProblem-solvingManaging ambiguity

Company Brief

Deepgram

Industry: API Platforms

Company Size: Medium (51 to 250 employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series C

Headquarters: San Francisco, United States

Founded: 2015

Glassdoor: 4.5

Website LinkedIn Glassdoor