Baseten Series E

Forward Deployed Engineer

San Francisco, CA On-site Added Jun 18

About the role

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE As a Forward Deployed Engineer at Baseten, you will partner directly with customers to architect, build, and deploy high-scale production AI applications on Baseten’s platform. You’ll own the journey with customers from initial exploration to production deployment, translating ambiguous business goals into reliable, observable services with clear quality, latency, and cost outcomes. This role is a great fit for entrepreneurial engineers who want a front-row view into how modern companies adopt AI at scale and who enjoy working across product, software development, performance engineering, and customer-facing implementations. To be clear, this is an engineering role with hands-on coding and software development that also includes aspects of product management, technical customer success, and pre-sales solution engineering mixed in. EXAMPLE INITIATIVES Take a look at these blog posts written by members of our Forward Deployed Engineering team: - Forward Deployed Engineering on the frontier of AI https://www.baseten.co/blog/forward-deployed-engineering/ - The fastest, most accurate Whisper transcription https://www.baseten.co/blog/the-fastest-most-accurate-and-cost-efficient-whisper-transcription/ - Deploy production-ready model servers from Docker images https://www.baseten.

Industry

AI/ML Infrastructure

Top skills for this role

  • ML inference and production model deployment
  • 2. Systems engineering for GPU infrastructure
  • 3. Customer-facing technical ownership for enterprise AI

Languages

Python (inferred)

Frameworks & tools

ML inference infrastructuremodel servingGPU optimization

AI / ML skills

ML model inferenceproduction AI deploymentGPU schedulingmodel optimization

Customer skills

Customer deployment of ML inference systems in production; translating model requirements to production solutions

Domain knowledge

AI/ML inference infrastructure; enterprise model deployment; GPU compute

Travel: not specified
Equity: not specified

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