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: 8 hours agoStatus: Live

Job Summary

Hands-on, field-based engineer embedding with customers to turn complex AI problems into production systems. You’ll ship code, run benchmarks, architect deployments, and lead executive-level conversations on architecture and business outcomes, while building POCs/MVPs and driving product improvements at AI-native customers and partners.

Location: New York, San Mateo

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Build end-to-end POCs and MVPs alongside customer engineering teams, working inside their codebases, infrastructure, and constraints.
•For customers whose core product is built on GenAI, architect the inference foundations that capability depends on, and size deployments so they can scale in their market without infrastructure becoming the bottleneck.
•Run load tests and establish latency, throughput, and cost baselines against realistic customer traffic profiles, and tune deployments to hit those targets.
•Deploy and validate new model families on inference frameworks (vLLM, SGLang), determining optimal shapes, quantization configs, and serving patterns across workloads.
•Lead structured discovery conversations to unpack customer pain points, constraints, and success criteria before proposing solutions and own the technical relationship from first engagement through production deployment.

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: Forward Deployed Engineer, Applied AI Engineer, Solutions Architect, ML Engineer with field exposure, or technical founder.
•Demonstrated ability to build production software with customers, not just advise on it. You have shipped code running in someone else’s production environment.
•Strong Python skills. Comfortable reading, writing, and debugging production code. Familiarity with Kubernetes and infrastructure engineering.
•Working knowledge of the LLM stack: inference trade-offs, model serving, fine-tuning workflows (SFT at minimum; DPO/RFT a strong plus).
•Experience with cloud infrastructure (AWS, Azure, GCP) and deploying models on GPU infrastructure.

Experience:5+ yearsAIInfrastructureGenAILLM

Skills:Problem-solvingCommunicationCollaborationStakeholder managementPresentation

Languages:English

Tech Stack:PythonKubernetesVLLMSGLangTensorRT-LLMAWSAzureGCPGPUSFTDPORFT

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: 8 hours agoStatus: Live

Job Summary

Location: New York, San Mateo

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Build end-to-end POCs and MVPs alongside customer engineering teams, working inside their codebases, infrastructure, and constraints.
•For customers whose core product is built on GenAI, architect the inference foundations that capability depends on, and size deployments so they can scale in their market without infrastructure becoming the bottleneck.
•Run load tests and establish latency, throughput, and cost baselines against realistic customer traffic profiles, and tune deployments to hit those targets.
•Deploy and validate new model families on inference frameworks (vLLM, SGLang), determining optimal shapes, quantization configs, and serving patterns across workloads.
•Lead structured discovery conversations to unpack customer pain points, constraints, and success criteria before proposing solutions and own the technical relationship from first engagement through production deployment.

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: Forward Deployed Engineer, Applied AI Engineer, Solutions Architect, ML Engineer with field exposure, or technical founder.
•Demonstrated ability to build production software with customers, not just advise on it. You have shipped code running in someone else’s production environment.
•Strong Python skills. Comfortable reading, writing, and debugging production code. Familiarity with Kubernetes and infrastructure engineering.
•Working knowledge of the LLM stack: inference trade-offs, model serving, fine-tuning workflows (SFT at minimum; DPO/RFT a strong plus).
•Experience with cloud infrastructure (AWS, Azure, GCP) and deploying models on GPU infrastructure.

Experience:5+ yearsAIInfrastructureGenAILLM

Skills:Problem-solvingCommunicationCollaborationStakeholder managementPresentation

Languages:English

Tech Stack:PythonKubernetesVLLMSGLangTensorRT-LLMAWSAzureGCPGPUSFTDPORFT

Company Brief

Fireworks AI

Industry: SaaS

Website