Archer

1 month ago

Senior AI Systems Engineer

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Architect, deploy, and manage infrastructure services that power large-scale AI model training and low-latency inference. Build and maintain MLOps tooling and workflows using MLflow to streamline the AI development lifecycle. Optimize multi-cloud compute scheduling with GPU/bare-metal resources, and use containerization and Kubernetes to run and monitor production systems. Collaborate with AI researchers and software engineers to productionize models and debug performance bottlenecks.

Location: San Jose

Workplace: Onsite

Employment Type: Full time

Job Function: IT Operations (Systems/Network Admin)

Seniority: Mid level

Key Responsibilities

•Architect, deploy, and manage infrastructure services for large-scale AI model training and inference.
•Deploy, scale, and maintain resilient infrastructure for distributed training and low-latency inference.
•Maintain end-to-end MLOps tooling, including MLflow for experiment tracking and model registry.
•Optimize compute and inference by maximizing hardware utilization and managing multi-cloud compute scheduling for LLM serving.
•Partner with AI researchers and software engineers to productionize models, set up monitoring, and debug hardware-software performance bottlenecks.

Pay and Benefits

Salary: USD 160,000 - 180,000 annually

Key Requirements

•BS/MS/PhD in Computer Science, Software Engineering, or a related field.
•3+ years of professional software engineering experience focused on AI/ML systems, high-performance computing (HPC), or ML infrastructure.
•Experience with multi-cloud infrastructure, including AWS and AI-centric GPU/bare-metal clouds such as Nebius AI Cloud.
•Hands-on experience with Docker and production-grade orchestration with Kubernetes, plus cloud-agnostic cluster abstraction (e.g., SkyPilot) for multi-region GPU availability.
•Strong understanding of LLM architecture and scalable serving using frameworks such as vLLM and SGLang, plus experience building high-throughput AI data pipelines (SQL, NoSQL, Parquet).

Experience:3+ yearsAI/MLHigh-performance computingMLOpsMulti-cloudLLM serving

Education:Bachelor's in Computer Science, Software Engineering, or a related field

Skills:Cross-functional collaborationDebuggingPerformance optimizationSystems thinking

Languages:English

Tech Stack:AWSNebius AI CloudMLflowDockerKubernetesSkyPilotVLLMSGLangSQLNoSQLParquet

Eligibility

Work Authorization:Authorization required. Sponsorship not provided.

Company Brief

Archer

Develops electric vertical takeoff and landing (eVTOL) aircraft and urban air mobility systems to enable sustainable, intra-city air transportation for passengers and cargo.

Industry: Aerospace Manufacturing

Company Size: Large (251 to 1,000 employees)

Revenue: Pre-Revenue (USD 0)

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Palo Alto, United States

Founded: 2018

Website LinkedIn

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Archer

1 month ago

Senior AI Systems Engineer

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Location: San Jose

Workplace: Onsite

Employment Type: Full time

Job Function: IT Operations (Systems/Network Admin)

Seniority: Mid level

Key Responsibilities

•Architect, deploy, and manage infrastructure services for large-scale AI model training and inference.
•Deploy, scale, and maintain resilient infrastructure for distributed training and low-latency inference.
•Maintain end-to-end MLOps tooling, including MLflow for experiment tracking and model registry.
•Optimize compute and inference by maximizing hardware utilization and managing multi-cloud compute scheduling for LLM serving.
•Partner with AI researchers and software engineers to productionize models, set up monitoring, and debug hardware-software performance bottlenecks.

Pay and Benefits

Salary: USD 160,000 - 180,000 annually

Key Requirements

•BS/MS/PhD in Computer Science, Software Engineering, or a related field.
•3+ years of professional software engineering experience focused on AI/ML systems, high-performance computing (HPC), or ML infrastructure.
•Experience with multi-cloud infrastructure, including AWS and AI-centric GPU/bare-metal clouds such as Nebius AI Cloud.
•Hands-on experience with Docker and production-grade orchestration with Kubernetes, plus cloud-agnostic cluster abstraction (e.g., SkyPilot) for multi-region GPU availability.
•Strong understanding of LLM architecture and scalable serving using frameworks such as vLLM and SGLang, plus experience building high-throughput AI data pipelines (SQL, NoSQL, Parquet).

Experience:3+ yearsAI/MLHigh-performance computingMLOpsMulti-cloudLLM serving

Education:Bachelor's in Computer Science, Software Engineering, or a related field

Skills:Cross-functional collaborationDebuggingPerformance optimizationSystems thinking

Languages:English

Tech Stack:AWSNebius AI CloudMLflowDockerKubernetesSkyPilotVLLMSGLangSQLNoSQLParquet

Eligibility

Work Authorization:Authorization required. Sponsorship not provided.

Company Brief

Archer

Develops electric vertical takeoff and landing (eVTOL) aircraft and urban air mobility systems to enable sustainable, intra-city air transportation for passengers and cargo.

Industry: Aerospace Manufacturing

Company Size: Large (251 to 1,000 employees)

Revenue: Pre-Revenue (USD 0)

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Palo Alto, United States

Founded: 2018

Website LinkedIn