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Speech Signal Processing Jobs in California (NOW HIRING)

Masimo

Sr Engineer, AI/Machine Learning

Irvine, CA

$140K - $170K/yr

... speech/audio and image/video. The Sr Engineer, AI & ML will also closely work with our software ... At least 3+ years of experience in AI/ML, statistical signal processing, and deep learning ...

Masimo

Sr Engineer, AI/Machine Learning

Irvine, CA · On-site

$140K - $170K/yr

... speech/audio and image/video. The Sr Engineer, AI & ML will also closely work with our software ... At least 3+ years of experience in AI/ML, statistical signal processing, and deep learning ...

David AI

Staff Full Stack Engineer

San Francisco, CA · On-site

$195K - $315K/yr

Educational or professional experience with digital signal processing and a deep understanding of speech. * Experience building and deploying ML models in a production environment. * Led (managed or ...

David AI

Staff Product Engineer

San Francisco, CA · On-site

$200K - $250K/yr

Educational or professional experience with digital signal processing and a deep understanding of speech. * Experience building and deploying ML models in a production environment. * Led (managed or ...

David AI

Product Engineer

San Francisco, CA · On-site

$170K - $240K/yr

Educational or professional experience with digital signal processing and a deep understanding of speech. * Experience building and deploying ML models in a production environment. * Led (managed or ...

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Speech Signal Processing information

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$15

$43

$68

How much do speech signal processing jobs pay per hour?

As of Jul 27, 2026, the average hourly pay for speech signal processing in California is $43.34, according to ZipRecruiter salary data. Most workers in this role earn between $35.58 and $51.01 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Speech Signal Processing Engineer, and why are they important?

To thrive as a Speech Signal Processing Engineer, you need a solid background in digital signal processing, mathematics, and programming, usually supported by a degree in electrical engineering, computer science, or a related field. Familiarity with tools and languages such as MATLAB, Python, TensorFlow, and experience with speech recognition frameworks is typically required. Strong analytical thinking, problem-solving abilities, and effective communication skills are important soft skills for this position. These competencies are essential for developing robust speech systems, ensuring accurate processing, and collaborating efficiently within multidisciplinary teams.

What is speech signal processing?

Speech signal processing is a field of study focused on analyzing, modifying, and synthesizing speech signals using digital techniques. It involves tasks such as noise reduction, speech recognition, speaker identification, and speech synthesis. Professionals in this area use mathematical algorithms and computer software to process recorded or live audio to improve clarity, extract information, or enable human-computer interactions. The applications of speech signal processing are widespread in telecommunications, assistive technology, and voice-activated systems.

What are some typical projects or tasks that a professional in Speech Signal Processing might work on within a multidisciplinary team?

As a Speech Signal Processing professional, you may collaborate with linguists, software engineers, and data scientists on projects such as developing automatic speech recognition (ASR) systems, enhancing voice assistants, or improving noise reduction algorithms. Daily tasks often include analyzing large datasets of speech, designing and testing algorithms, and integrating your solutions into larger products. Team-based work is common, requiring strong communication skills to bridge technical and non-technical perspectives. The dynamic nature of the field also means you'll often participate in research and experimentation to push the boundaries of what voice technology can achieve.

What is the difference between Speech Signal Processing vs Speech Recognition Engineer?

AspectSpeech Signal ProcessingSpeech Recognition Engineer
Required CredentialsBachelor's or Master's in Electrical Engineering, Computer Science, or related fieldsBachelor's or Master's in similar fields, often with specialization in AI or machine learning
Work EnvironmentResearch labs, tech companies, academia, focusing on audio data analysisTech companies, startups, focusing on developing speech-to-text systems
Industry UsageUsed in audio enhancement, noise reduction, speech codingApplied in voice assistants, transcription services, voice-controlled devices

Speech Signal Processing involves analyzing and improving speech audio signals, while Speech Recognition Engineers focus on converting speech into text. Both roles require similar technical backgrounds but differ in their primary objectives and applications within the industry.

What are popular job titles related to Speech Signal Processing jobs in California? For Speech Signal Processing jobs in California, the most frequently searched job titles are:
What job categories do people searching Speech Signal Processing jobs in California look for? The top searched job categories for Speech Signal Processing jobs in California are:
Speech Signal Processing jobs near you
Infographic showing various Speech Signal Processing job openings in California as of July 2026, with employment types broken down into 78% Full Time, 16% Part Time, 1% Temporary, 4% Contract, and 1% Nights. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $90,150 per year, or $43.3 per hour.

Deep Learning Scientist, Speech Synthesis

Vailexa

Santa Clara, CA

Full-time

Posted 5 days ago

Job description

Build More Than Just a Career. Build Your Future.

At Vailexa, we're not just hiring — we're building thinkers, creators, and future leaders.

We believe in giving people the space to grow, the freedom to think, and the opportunity to create real impact from day one. If you're someone who wants to learn fast, take ownership, and grow beyond limits, you'll feel right at home here.

Key Responsibilities

  • Train speech synthesis mel spectrogram and vocoder models
  • Measure and benchmark model performance across use cases
  • Maintain and enhance text to speech evaluation systems
  • Analyze model accuracy and bias and recommend improvements
  • Improve processes related to speech data preparation, augmentation, and filtering
  • Develop and refine training datasets for speech models
  • Characterize performance and quality metrics across different platforms
  • Collaborate with cross functional teams to deliver new product features
  • Participate in code development, design reviews, and test planning
  • Identify issues, propose solutions, and contribute to continuous innovation

Required Qualifications

  • Master's degree or PhD in Computer Science, Electrical Engineering, Artificial Intelligence, Applied Mathematics, Linguistics, or Computational Linguistics or equivalent experience
  • Minimum of 5 years of relevant experience
  • Strong programming skills in Python
  • Solid understanding of programming fundamentals and software design
  • Deep knowledge of machine learning and deep learning techniques including CNN, RNN, LSTM, and Transformers
  • Experience applying deep learning to speech synthesis, large language models, and speech to speech translation
  • Hands on experience with speech technologies such as speech synthesis and voice cloning
  • Experience training speech models
  • Proficiency with PyTorch deep learning frameworks
  • Knowledge of speech signal processing techniques including FFT, MFCC, and mel spectrograms
  • Familiarity with version control tools such as Git, Gerrit, or GitLab
  • Strong collaboration and communication skills in a matrixed environment

Preferred Qualifications

  • Fluency in one or more languages such as Spanish, Mandarin, German, Japanese, Russian, French, Arabic, Hindi, Korean, Italian, or Portuguese
  • Experience with multilingual or code switched text to speech systems
  • Experience with voice cloning and cross lingual voice cloning
  • Knowledge of text normalization and inverse text normalization using neural networks or WFST
  • Experience working with grapheme to phoneme systems for multiple languages
  • Interest in linguistics, phonetics, and language technologies
  • Strong C plus plus programming skills
  • Familiarity with GPU technologies such as CUDA, cuDNN, or TensorRT
  • Experience deploying machine learning models to cloud, data center, or embedded systems

Ready to take the next step?

If you're excited about this role and ready to grow with a team that values ambition, ideas, and impact — we'd love to hear from you.

👉 Apply now and start building your journey with Vailexa.