Forward Deployed ML Engineer: Shape AI Infra at Scale

Fdetimes

New York (NY)

In loco

USD 180.000 - 280.000

Tempo pieno

14 giorni+

Una candidatura completa in un minuto

Curriculum e lettera di presentazione personalizzati, pronti da inviare.

Supera i filtri ATS

Descrizione del lavoro

Modal is seeking Forward Deployed ML Engineers to work at the intersection of deep technical work and direct customer impact. You’ll partner with leading AI companies to help achieve state-of-the-art performance on demanding workloads like LLM serving, model training, and data pipelines.

You’ll join a world-class team, collaborating with product and sales to deliver the platform as both an engineer and a product stakeholder.

Competenze

  • 2+ years of professional ML engineering experience.
  • Experience in inference optimization or ML infrastructure.
  • Hands-on model training or GPU programming.
  • Familiar with AI serving and training toolchains.
  • Strong communication skills with technical leadership.
  • Willing to work in-person in NYC, SF, or Stockholm.

Mansioni

  • Architect and optimize production AI workloads.
  • Contribute to open-source projects and publish content.
  • Collaborate with product and sales teams as an engineer and a product stakeholder.
  • Build trusted relationships with CTOs and ML leads at frontier AI companies.
  • Conduct technical demos, experiments, and proofs of concept.

Conoscenze

ML engineering
Inference optimization
Model training
GPU programming
ML infrastructure
Serving toolchains
Training toolchains
Technical communication
Customer interaction

Strumenti

vLLM
SGLang
slime
verl
TRL

Descrizione del lavoro

Modal is seeking Forward Deployed ML Engineers to work at the intersection of deep technical work and direct customer impact. You’ll partner with leading AI companies to help achieve state-of-the-art performance on demanding workloads like LLM serving, model training, and data pipelines.

You’ll join a world-class team, collaborating with product and sales to deliver the platform as both an engineer and a product stakeholder.

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