Software Engineer – Applications

Elorian AI

. Design, build, and deploy low-latency, scalable application architectures integrating Glimpse into complex enterprise data pipelines and high-throughput workflows .

Posted 10/31/2026full-timePalo Alto • California • United StatesMid-LevelSenior💰 $250,000 - $400,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying low-latency, scalable application architectures, particularly in multimodal systems and model evaluation pipelines. Proficient in Python and familiar with modern cloud architecture and API design, with a strong ability to communicate complex technical concepts effectively.

Highest-signal resume keywords

Python ProgrammingMultimodal Application DevelopmentModel Evaluation PipelinesCloud ArchitectureAPI Design

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Hard Skills

PythonTypeScriptGoRustModel Fine-TuningBenchmarking ML ModelsApplication Architecture DesignData Pipeline OptimizationOrchestration LogicHigh-Performance Software Development

Soft Skills

Technical CommunicationProblem-Solving

Tools & Technologies

GlimpseOpen-Source AI ToolingDeveloper SDK ComponentsStreaming ProtocolsVector Indexing

Industry Keywords

LLMMultimodal ModelsVision-Language ModelsAI Developer PlatformML Infrastructure

Tech Stack

Tools & technologies

CloudPythonRustTypeScriptGo

About the role

Key responsibilities & impact

Design, build, and deploy low-latency, scalable application architectures integrating Glimpse into complex enterprise data pipelines and high-throughput workflows
Create open-source reference implementations, production-ready demo applications, developer tooling, and SDK components
Design and implement evaluation pipelines and benchmarking harnesses to test Glimpse against other frontier multimodal models on real-world visual datasets
Isolate and resolve bottlenecks across application pipelines, data ingestion layers, model inference APIs, and prompt/orchestration logic
Serve as the core technical architect for design-partner engineering teams, guiding technical discovery, proof-of-concept development, and production deployment
Translate application failure modes, edge cases, and performance requirements into specifications for research and model infrastructure teams
Work directly with founders, early enterprise partners, and the internal research team
Build the engineering bridge between multimodal research and production deployments

Requirements

What you’ll need

5+ years of experience building and shipping high-performance, production software in Python
Ideally TypeScript or Go/Rust experience
Experience building complex LLM/multimodal application systems beyond basic API calls
Experience with agentic workflows, structured tool-use frameworks, model evaluation pipelines, or orchestration layers for vision-language models
Hands-on experience evaluating, fine-tuning, or benchmarking ML models
Ability to differentiate between model failure modes, pipeline errors, and data-quality issues
Experience as a founding engineer, startup core contributor, or forward-deployed engineer highly valued
Familiarity with modern cloud architecture, API design, vector/multimodal indexing, streaming protocols, and high-volume image/video data pipelines under tight latency and cost constraints
Ability to communicate complex architectural tradeoffs clearly to internal research teams and external engineering leaders
Prior experience at a foundation model provider, AI developer platform, or ML infrastructure company is nice to have
Direct experience building multimodal applications in vision-heavy verticals is nice to have
Experience developing public developer APIs, open-source AI tooling, or developer ecosystems is nice to have
Ability to work from the Palo Alto, CA office on a regular basis

Benefits

Comp & perks

significant equity
comprehensive health insurance
perks