Software Engineer (Full-Stack) at Latent AI

San Francisco, California, United States

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Healthcare, Health TechIndustries

Requirements

Generalist mindset, thriving on owning projects end-to-end
High standards, proficiency with keyboard shortcuts, and passion for automation to increase leverage
Experience in both frontend and backend development
Product focus: ability to work with customers, define product specs, and iterate quickly
Bias for action: willingness to jump into tasks without waiting for others
Deep proficiency with TypeScript and React
Strong experience with Redis, PostgreSQL, Temporal, and Kafka
Proven system design skills to manage complexity with simple abstractions
Excitement about working five days per week in San Francisco office

Responsibilities

Drive product initiatives and manage technical delivery across the entire application
Design, build, and deploy new features from API development to user interface implementation (end-to-end delivery)
Architect and manage solution complexity, define standards, and create simple abstractions
Dive deep into Prior Authorizations, Patient Interactions, and EHR Integrations for healthcare improvements
Integrate and utilize core Clinical AI Models for user-facing features

Skills

Full-Stack Development

Frontend Development

Backend Development

API Development

Database

User Interface

System Architecture

EHR Integration

AI Implementation

Latent AI

Optimizes AI for edge computing applications

About Latent AI

Latent AI focuses on enhancing artificial intelligence for edge computing, which involves processing data close to where it is generated, like on smartphones and IoT devices. Their main product is an edge MLOps workflow that automates and simplifies the deployment of AI models on these devices, ensuring they are efficient, secure, and require minimal maintenance. This company stands out from competitors by specifically targeting the edge computing market and providing a software development kit (SDK) called Latent LEIP, which aids developers in creating and deploying AI models. The goal of Latent AI is to make AI more accessible and efficient for applications that need real-time data processing, such as in autonomous vehicles and smart cities.

Menlo Park, CaliforniaHeadquarters

2018Year Founded

$21.9MTotal Funding

SERIES_ACompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine LearningIndustries

51-200Employees

Risks

Competition from tech giants like Google and Amazon threatens Latent AI's market share.

Rapid AI advancements may outpace Latent AI's current capabilities, requiring continuous innovation.

Dependency on key partnerships, like Booz Allen, poses risks if relationships change.

Differentiation

Latent AI specializes in optimizing AI for edge computing applications.

Their edge MLOps workflow ensures efficient, secure AI model deployment on edge devices.

Latent AI's SDK, Latent LEIP, streamlines AI model creation and deployment for developers.

Upsides

Growing interest in federated learning enhances privacy and efficiency for edge AI.

The rise of TinyML aligns with Latent AI's focus on resource-constrained edge devices.

5G technology adoption boosts data transmission speed for Latent AI's solutions.

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