Want to get hired at Speechify?
Software Engineer iOS Core Product
Speechify
Cambridge, Massachusetts, United StatesOn Site
Original Job Summary
About Speechify
The mission of Speechify is to ensure that reading is never a barrier to learning. Over 50 million people use Speechify’s text-to-speech products across multiple platforms including iOS, Android, Mac, Chrome, and Web.
Position Overview
As a Software Engineer iOS Core Product at Speechify, you will work in a fast-paced, flat organization alongside experts from leading companies and institutions. You will be responsible for building robust machine learning inference pipelines and improving user experiences.
Key Responsibilities
- Collaborate with ML researchers, engineers, and product managers.
- Deploy and operate core ML inference workloads.
- Introduce techniques to improve performance and efficiency.
- Develop tools to monitor and address system bottlenecks.
Candidate Requirements
- Experience with Python-based services.
- Proven track record in operating critical production services.
- Familiarity with public cloud environments; GCP is preferred.
- Knowledge of Infrastructure as Code, Docker, and containerized deployments.
- Preferred experience with Kubernetes and deploying ML models.
What We Offer
A dynamic, distributed work environment that values innovation, autonomy, and impact. Enjoy competitive compensation, a supportive culture, and a chance to work on products that change lives.
Key skills/competency
- Python
- Cloud
- ML Deployment
- Containerization
- Kubernetes
- Performance
- Infrastructure
- Tooling
- Collaboration
- Problem-solving
How to Get Hired at Speechify
🎯 Tips for Getting Hired
- Customize Your Resume: Tailor your application with relevant technical experiences.
- Highlight Key Skills: Showcase your Python, cloud, and containerization expertise.
- Prepare for Interviews: Practice technical and behavioral questions.
- Research Speechify: Understand their mission and distributed work culture.
📝 Interview Preparation Advice
Technical Preparation
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Review Python service deployment methods.
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Practice cloud environment configuration, especially GCP.
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Study Docker and container orchestration.
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Learn Kubernetes high-availability deployments.
Behavioral Questions
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Describe a challenging problem you solved.
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Explain your teamwork experience in distributed settings.
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Discuss handling high-pressure project deadlines.
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Share how you improve communication skills.