Software Engineer, iOS Core Product
@ Speechify

San Diego, California, United States
$150,000
On Site
Full Time
Posted 6 hours ago

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Job Details

Overview

Speechify is on a mission to remove reading barriers using text-to-speech. Over 50 million people rely on our products, including our iOS app, to convert text into audio and improve learning. Speechify has been recognized by Google and Apple, and we operate in a 100% distributed setting with a team from leading companies and universities.

Role and Responsibilities

As a Software Engineer, iOS Core Product at Speechify, you will work closely with machine learning researchers, engineers, and product managers. You will deploy, operate, and improve our AI Voices serving pipeline by:

  • Deploying and managing core ML inference workloads.
  • Introducing new techniques, tools, and architectures to enhance performance.
  • Building tools for monitoring bottlenecks and instability.
  • Designing and implementing practical solutions to critical issues.

Ideal Candidate Profile

The ideal candidate has strong technical skills and hands-on experience with Python-based services, critical production service operations, public cloud environments (especially GCP), and infrastructure tools such as Code, Docker, and containerized deployments. Experience with high-availability applications on Kubernetes and deploying ML models to production is a plus.

What We Offer

Join a dynamic environment where your contributions directly shape product decisions. You will benefit from autonomy, a focus on creativity, competitive compensation, and the privilege of impacting lives through technology.

Key skills/competency

  • Python
  • Cloud (GCP)
  • Docker
  • Kubernetes
  • ML models
  • Infrastructure as Code
  • Performance optimization
  • Monitoring
  • Production service
  • User experience

How to Get Hired at Speechify

🎯 Tips for Getting Hired

  • Customize your resume: Tailor your skills to Speechify's requirements.
  • Showcase technical projects: Highlight Python and cloud experience.
  • Emphasize collaboration: Detail teamwork and communication skills.
  • Prepare for interviews: Review ML, Docker, and Kubernetes topics.

📝 Interview Preparation Advice

Technical Preparation

Review Python coding challenges.
Study GCP and cloud concepts.
Practice deploying Docker containers.
Familiarize with Kubernetes basics.

Behavioral Questions

Describe conflict resolution in team settings.
Explain decision-making under pressure.
Discuss communication in remote work.
Share experiences of leadership in projects.

Frequently Asked Questions