Wispr Logo

Wispr

ML Engineer

Reposted 3 Months Ago
In-Office
San Francisco, CA, USA
250K-400K Annually
Mid level
In-Office
San Francisco, CA, USA
250K-400K Annually
Mid level
As a ML Engineer at Wispr, you will design features for a voice interface, optimize ML inference, and scale personalization of speech models.
The summary above was generated by AI
About Wispr

Wispr is an AI research and product company building the voice interface for computing. AI can now reason, code, and act. Yet, humans still do the work of the interface. We think that’s backwards.
Our first products are Flow, which lets you speak naturally in any application, and Notetaker, which builds context across conversations. We’re building toward an interface that can perceive, understand, and take action with earned trust. That means solving hard problems across models, systems, and product - and caring about the final human experience as deeply as the technology underneath it.


We’re a talent-dense team that holds strong opinions, tests them quickly, and builds technology that sparks joy. Our goal is to build the first voice interface used every day by a billion people.

About the role

As a ML engineer at Wispr, you’ll play a crucial role in building the first capable, habit forming voice interface that scales to a billion users. Members of our technical staff are responsible for prototyping and designing new features of our voice interface, building infrastructure to handle <500ms LLM inference for millions of requests from everywhere around the world, and scaling the personalization of our speech models and LLMs with fine-tuning and RL.

What are we looking for?
  • Previous founding or startup experience

  • Experience optimizing ML inference or engineering systems for research teams

  • Fluency in Python and LLM development

  • Attention to detail and eagerness to learn

  • Aptitude and clarity of thought

  • Creativity, excellence in engineering, and code velocity

Logistics

We sponsor H1B, O1, EB1, L1, STEM OPT, and more. We can't guarantee sponsorship for every role, but if we make you an offer we'll make every reasonable effort, with help from our immigration law firm.
We strongly encourage you to apply even if you don't meet every qualification. The strongest candidates we meet rarely do, so don't exclude yourself prematurely. We're rethinking how humans interact with AI, and doing that well demands diversity of perspective and experience.
We're committed to a fair and accessible interview process. If you need any accommodations or adjustments, please let us know.

HQ

Wispr San Francisco, California, USA Office

San Francisco, CA, United States

Wispr South San Francisco, California, USA Office

400 Oyster Point Blvd, South San Francisco, CA, United States, 94080

Similar Jobs

Yesterday
Easy Apply
Hybrid
San Francisco, CA, USA
Easy Apply
228K-317K Annually
Senior level
228K-317K Annually
Senior level
Fintech • Payments • Financial Services
Design, productionize, and operate machine learning models and rule-based decision systems for credit underwriting. Build scalable pipelines for feature engineering, training, validation, deployment, monitoring, and continuous improvement. Optimize ML performance, integrate solutions with products, collaborate with engineering, CreditOps, risk, and data teams, and promote strong software engineering and MLOps practices across product teams.
Top Skills: AirflowArgo WorkflowsDockerGrafanaJavaKubernetesLightgbmMlflowPandasPrometheusPysparkPythonPyTorchTensorFlowTrino SqlXgboost
5 Days Ago
In-Office
Milpitas, CA, USA
178K-361K Annually
Expert/Leader
178K-361K Annually
Expert/Leader
Artificial Intelligence • Cloud • Information Technology • Consulting
Lead end-to-end delivery of production AI and machine learning use cases, including LLM and agentic systems. Define scalable architectures, evaluation frameworks, guardrails, monitoring, and operational practices. Create reusable AI engineering patterns, partner with business and technical stakeholders, influence adoption, guide architecture decisions, and mentor engineers. Help establish team governance, prioritization, and delivery practices while ensuring reliable, secure, measurable business impact.
Top Skills: Agentic AiAi GovernanceArtificial IntelligenceCloud-NativeData PipelinesDeep LearningGenerative AiHybrid CloudLarge Language ModelsLlmopsMachine LearningMlopsNatural Language ProcessingResponsible Ai
6 Days Ago
Hybrid
2 Locations
230K-286K Annually
Senior level
230K-286K Annually
Senior level
Fintech • Machine Learning • Payments • Software • Financial Services
Design, build, deploy, scale, and maintain machine learning models and platforms in production. Responsibilities include developing ML infrastructure, data pipelines, cloud architectures, distributed systems, model monitoring, retraining, testing, CI/CD, and responsible AI practices. The role collaborates with Product, Data Science, and Agile engineering teams while applying advanced modeling techniques and managing large-scale containerized ML systems.
Top Skills: AWSAzureC++Ci/CdGCPGoJavaKubernetesNumpyPandasPythonPyTorchRayScalaScikit-LearnSparkTensorFlow

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account