1 month ago

AI Field Engineer - Enterprise

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 7 hours agoStatus: Live

Job Summary

Embed with enterprise customers to turn GenAI use cases into production-ready systems. Build end-to-end POCs and MVPs alongside customer engineering teams, architect inference foundations, and validate performance via load testing and latency/cost tuning. Guide model selection and fine-tuning strategy, deploy new model families on inference frameworks, and lead discovery conversations with ML engineers and VP-level stakeholders. Translate recurring field pain points into product improvements and reusable deployment patterns.

Location: San Mateo, New York

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Build end-to-end POCs and MVPs with customer engineering teams, working inside their codebases, infrastructure, and constraints.
•Architect inference foundations, size deployments, and run load tests to establish and tune for latency, throughput, and cost targets.
•Deploy and validate new model families on inference frameworks (vLLM, SGLang), selecting shapes, quantization configs, and serving patterns.
•Advise on model selection and fine-tuning strategy (SFT, DPO, RFT), and build/run fine-tuning pipelines with evaluation tied to production-quality metrics.
•Lead discovery and stakeholder conversations, provide ongoing technical ownership from engagement through production deployment, and feed field learnings into product roadmap and tooling.

Pay and Benefits

Salary: USD 200,000 - 260,000 annually

Equity and Bonus:Equity

Key Requirements

•5+ years in a hands-on, customer-facing technical role (e.g., Forward Deployed Engineer, Applied AI Engineer, Solutions Architect, ML Engineer with field exposure, or technical founder).
•Demonstrated ability to build production software with customers, including shipping code that runs in a customer’s production environment.
•Strong Python skills with comfort reading, writing, and debugging production code, plus familiarity with Kubernetes and infrastructure engineering.
•Working knowledge of the LLM stack, including inference trade-offs, model serving, and fine-tuning workflows (SFT; DPO/RFT a plus).
•Experience with cloud infrastructure (AWS, Azure, GCP) and deploying models on GPU infrastructure.

Experience:GenAI

Skills:CommunicationStakeholder managementRelationship buildingDebugging

Tech Stack:PythonKubernetesAWSAzureGCPGPU infrastructureVLLMSGLangTensorRT-LLMPyTorchAWS BedrockSageMakerAzure AI FoundryGCP Vertex

Company Brief

Fireworks AI

Develops AI-driven tools to generate and optimize visual marketing content for brands and creators, automating production of short-form videos and multimedia assets for social platforms to improve engagement and scale creative workflows.

Industry: SaaS

Website

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Fireworks AI

1 month ago

AI Field Engineer - Enterprise

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 7 hours agoStatus: Live

Job Summary

Location: San Mateo, New York

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Build end-to-end POCs and MVPs with customer engineering teams, working inside their codebases, infrastructure, and constraints.
•Architect inference foundations, size deployments, and run load tests to establish and tune for latency, throughput, and cost targets.
•Deploy and validate new model families on inference frameworks (vLLM, SGLang), selecting shapes, quantization configs, and serving patterns.
•Advise on model selection and fine-tuning strategy (SFT, DPO, RFT), and build/run fine-tuning pipelines with evaluation tied to production-quality metrics.
•Lead discovery and stakeholder conversations, provide ongoing technical ownership from engagement through production deployment, and feed field learnings into product roadmap and tooling.

Pay and Benefits

Salary: USD 200,000 - 260,000 annually

Equity and Bonus:Equity

Key Requirements

•5+ years in a hands-on, customer-facing technical role (e.g., Forward Deployed Engineer, Applied AI Engineer, Solutions Architect, ML Engineer with field exposure, or technical founder).
•Demonstrated ability to build production software with customers, including shipping code that runs in a customer’s production environment.
•Strong Python skills with comfort reading, writing, and debugging production code, plus familiarity with Kubernetes and infrastructure engineering.
•Working knowledge of the LLM stack, including inference trade-offs, model serving, and fine-tuning workflows (SFT; DPO/RFT a plus).
•Experience with cloud infrastructure (AWS, Azure, GCP) and deploying models on GPU infrastructure.

Experience:GenAI

Skills:CommunicationStakeholder managementRelationship buildingDebugging

Tech Stack:PythonKubernetesAWSAzureGCPGPU infrastructureVLLMSGLangTensorRT-LLMPyTorchAWS BedrockSageMakerAzure AI FoundryGCP Vertex

Company Brief

Fireworks AI

Industry: SaaS

Website