1 month ago

AI Field Engineer - AI Natives

✓ 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 Fireworks’ most ambitious AI-native customers and technology partners to turn complex GenAI problems into production systems. Build end-to-end POCs and MVPs, architect inference foundations, and tune deployments using inference frameworks like vLLM and SGLang. Lead discovery conversations, run load tests for latency/throughput/cost, guide fine-tuning strategy (SFT/DPO/RFT), and translate field learnings into product improvements.

Location: San Mateo, New York

Workplace: Onsite

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 inside their codebases, infrastructure, and constraints.
•Architect inference foundations and size deployments to scale without infrastructure becoming a bottleneck.
•Run load tests to establish latency, throughput, and cost baselines, then tune deployments to hit targets.
•Deploy and validate model families using inference frameworks (vLLM, SGLang), selecting shapes, quantization configs, and serving patterns.
•Lead discovery conversations and translate customer pain points into product improvements while feeding deployment patterns and failure modes back to the product roadmap.

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 such as 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 production environment.
•Strong Python skills with experience 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 is a plus).
•Experience with cloud infrastructure (AWS, Azure, GCP) and deploying models on GPU infrastructure, with exceptional communication for executive-level discovery.

Experience:GenAI

Skills:CommunicationStakeholder managementProblem-solvingDebugging

Tech Stack:PythonKubernetesAWSAzureGCPVLLMSGLangTensorRT-LLMSFTDPORFTPyTorchAzure AI FoundryAWS BedrockSageMakerGCP VertexQuantizationLoad testing

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 - AI Natives

✓ 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

Workplace: Onsite

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 inside their codebases, infrastructure, and constraints.
•Architect inference foundations and size deployments to scale without infrastructure becoming a bottleneck.
•Run load tests to establish latency, throughput, and cost baselines, then tune deployments to hit targets.
•Deploy and validate model families using inference frameworks (vLLM, SGLang), selecting shapes, quantization configs, and serving patterns.
•Lead discovery conversations and translate customer pain points into product improvements while feeding deployment patterns and failure modes back to the product roadmap.

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 such as 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 production environment.
•Strong Python skills with experience 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 is a plus).
•Experience with cloud infrastructure (AWS, Azure, GCP) and deploying models on GPU infrastructure, with exceptional communication for executive-level discovery.

Experience:GenAI

Skills:CommunicationStakeholder managementProblem-solvingDebugging

Tech Stack:PythonKubernetesAWSAzureGCPVLLMSGLangTensorRT-LLMSFTDPORFTPyTorchAzure AI FoundryAWS BedrockSageMakerGCP VertexQuantizationLoad testing

Company Brief

Fireworks AI

Industry: SaaS

Website