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Audio Speech Machine Learning information

What are some common challenges faced when developing machine learning models for audio speech applications?

A key challenge in audio speech machine learning roles is dealing with diverse and noisy audio data, which can significantly affect model accuracy. Additionally, models must be robust to different accents, languages, and speaking styles, requiring large and varied datasets for training and validation. Collaboration with data engineers, linguists, and software developers is often necessary to ensure high-quality data pipelines and model integration into production systems. Staying updated with the latest research and optimizing models for real-time performance are also ongoing aspects of the role.

What is an audio speech machine learning engineer?

An Audio Speech Machine Learning Engineer is a specialized professional who designs, develops, and implements machine learning models that process and analyze audio and speech data. Their work involves tasks like speech recognition, speaker identification, and audio event detection by leveraging algorithms and large datasets. These engineers collaborate with data scientists, software developers, and linguists to create applications such as voice assistants, transcription tools, and automated customer service systems. Expertise in signal processing, deep learning frameworks, and programming languages like Python is crucial for this role.

What is the difference between Audio Speech Machine Learning vs Speech Data Analyst?

AspectAudio Speech Machine LearningSpeech Data Analyst
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of ML frameworksDegree in Data Analysis, Statistics, or related fields; experience with data tools
Work EnvironmentResearch labs, tech companies, AI startupsData analysis teams, research institutions, tech firms
Industry UsageDeveloping speech recognition, voice assistants, NLP applicationsAnalyzing speech datasets, improving speech models, reporting insights

Audio Speech Machine Learning focuses on developing algorithms for speech recognition and processing, often involving model training and AI development. Speech Data Analysts interpret speech data, generate insights, and support model improvements. Both roles require strong analytical skills, but their core tasks differ: one builds models, the other analyzes data.

What are the key skills and qualifications needed to thrive as an audio speech machine learning engineer, and why are they important?

To thrive as an Audio Speech Machine Learning Engineer, you need a solid background in machine learning, signal processing, and programming (typically Python), along with a relevant degree in computer science or a related field. Familiarity with tools like TensorFlow or PyTorch, audio processing libraries (such as Librosa), and experience with speech datasets and ASR systems are commonly required. Critical soft skills include problem-solving, innovation, and effective communication for collaborating with cross-functional teams. These skills are essential to develop accurate, scalable speech recognition systems that advance voice-driven technology.
What are popular job titles related to Audio Speech Machine Learning jobs in Nevada? For Audio Speech Machine Learning jobs in Nevada, the most frequently searched job titles are:
What job categories do people searching Audio Speech Machine Learning jobs in Nevada look for? The top searched job categories for Audio Speech Machine Learning jobs in Nevada are:
What cities in Nevada are hiring for Audio Speech Machine Learning jobs? Cities in Nevada with the most Audio Speech Machine Learning job openings:
Audio Speech Machine Learning jobs near you

Software Engineer, Platform - Las Vegas, NV, USA

Speechify

Las Vegas, NV • On-site

Full-time

Re-posted 4 days ago

Job description

The mission of Speechify is to make sure that reading is never a barrier to learning.
Over 50 million people use Speechify's text-to-speech products to turn whatever they're reading - PDFs, books, Google Docs, news articles, websites - into audio, so they can read faster, read more, and remember more. Speechify's text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.
Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting - Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.
Overview
The responsibilities of our Platform team include building and maintaining all backend services, including, but not limited to, payments, analytics, subscriptions, new products, text to speech, and external APIs.
This is a key role and ideal for someone who thinks strategically, enjoys fast-paced environments, is passionate about making product decisions, and has experience building great user experiences that delight users.
We are a flat organization that allows anyone to become a leader by showing excellent technical skills and delivering results consistently and fast. Work ethic, solid communication skills, and obsession with winning are paramount.
Our interview process involves several technical interviews and we aim to complete them within 1 week.
What You'll Do
  • Design, develop, and maintain robust APIs including public TTS API, internal APIs like Payment, Subscription, Auth and Consumption Tracking, ensuring they meet business and scalability requirements
  • Oversee the full backend API landscape, enhancing and optimizing for performance and maintainability
  • Collaborate on B2B solutions, focusing on customization and integration needs for enterprise clients
  • Work closely with cross-functional teams to align backend architecture with overall product strategy and user experience

An Ideal Candidate Should Have
  • Proven experience in backend development: TS/Node (required)
  • Direct experience with GCP and knowledge of AWS, Azure, or other cloud providers
  • Efficiency in ideation and implementation, prioritizing tasks based on urgency and impact
  • Preferred: Experience with Docker and containerized deployments
  • Preferred: Proficiency in deploying high availability applications on Kubernetes

What We Offer
  • A dynamic environment where your contributions shape the company and its products
  • A team that values innovation, intuition, and drive
  • Autonomy, fostering focus and creativity
  • The opportunity to have a significant impact in a revolutionary industry
  • Competitive compensation, a welcoming atmosphere, and a commitment to an exceptional asynchronous work culture
  • The privilege of working on a product that changes lives, particularly for those with learning differences like dyslexia, ADD, and more
  • An active role at the intersection of artificial intelligence and audio - a rapidly evolving tech domain

The United States Based Salary range for this role is: 140,000-200,000 USD/Year + Bonus + Stock depending on experience
Think you're a good fit for this job?
Tell us more about yourself and why you're interested in the role when you apply.
And don't forget to include links to your portfolio and LinkedIn.
Not looking but know someone who would make a great fit?
Refer them!
Speechify is committed to a diverse and inclusive workplace.
Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

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