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Speech Signal Processing Jobs in California (NOW HIRING)

Apple

Hearing Health Technologist

Cupertino, CA

$150K - $277K/yr

In-depth experience applying signal processing and machine learning techniques for audio enhancements in the context of speech communication or music listening. Familiarity with fundamental acoustic ...

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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 Aug 10, 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 skills and qualifications are needed for speech signal processing?

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 do speech signal processing professionals do?

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 August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $90,150 per year, or $43.3 per hour.

Research Scientist IV

PROLIM Global Corporation

Burlingame, CA • On-site

Full-time

Posted 29 days ago

Job description

Organization Overview
Reality Labs Research at Meta is a leading research organization of world-class researchers, developers, and engineers, who collaborate to actively create a future where virtual and augmented reality become as indispensable as today's smartphones and personal computers.
The mission of the Reality Labs Research Audio team is to engineer augmented audio that redefines human hearing capabilities. This will allow us to connect people by facilitating conversation in even the most challenging auditory environment.
Role Summary
We are seeking a contract applied research scientist specializing in building machine learning (ML) models that emulate auditory perception. This role is an integral part of our team, contributing to our research and development efforts. The ideal candidate will help us explore and understand individualized audio quality preferences and experiences, enabling us to tailor our technologies to meet unique user needs.
Responsibilities
  • Drive research on improved machine learning models for speech quality, run computational experiments and report findings.
  • Implement ML models that emulate aspects of human auditory perception.
  • Develop next-gen audio quality models.
  • Independently implement ML training pipelines, models, and evaluation frameworks.
  • Regularly report on project progress, dependencies and risks to stakeholders.
  • Support research scientists and engineers within the team.
  • Execute on applied coding tasks in support of the team's goals.

Minimum Qualifications
  • Interpersonal and communication skills, with strong attention to detail.
  • Proactive with ability to execute on multiple projects simultaneously.
  • Strong organizational and time management skills.
  • Track record of communicating research on ML perception in an academic or industrial setting.
  • Experience working in a fast-paced research and/or product development environment.
  • Experience with Python or other scientific programming languages.
  • Previous experience designing, training, and evaluating neural networks in Pytorch.
  • Experience working in a high performance computing environment.
  • Master's degree or equivalent experience in Computational Neuroscience, Cognitive Science, Electrical Engineering, Perception, Experimental Psychology, Audio Engineering, Acoustics, Computer Science, Computer Engineering, Biomedical Engineering, Computational Audiology or a related field.

Preferred Qualifications
  • PhD degree or equivalent experience.
  • Experience with modeling audio quality.

Top 3 Must-Have HARD Skills
  • Deep Learning for Audio/Speech Processing: The role requires building ML models for speech quality assessment and auditory perception. The candidate must have hands-on experience designing, training, and evaluating neural networks specifically for audio applications using PyTorch (TensorFlow, Keras much less desirable).
  • Psychoacoustic & Perceptual Modeling Expertise: The candidate must understand how humans perceive audio quality, including concepts like speech intelligibility, listening effort, speech degradation, and noise noticeability. This is critical for building models that accurately predict subjective Mean Opinion Scores (MOS) and enable features like Conversation Focus to be evaluated computationally rather than through time-consuming user studies.
  • ML Training Pipeline & Evaluation Framework Development: The role requires independently implementing end-to-end ML pipelines: data preparation, model training, hyperparameter tuning, and evaluation using metrics like MAE, Pearson correlation, SI-SDR, PESQ, STOI. Experience with HPC environments for large-scale training is essential.

Good-to-Have Skills
  • Binaural audio processing and spatial audio quality assessment
  • Speech enhancement experience (noise suppression, dereverberation, speaker separation)
  • Experience with audio-visual ML models (multi-modal learning)
  • Familiarity with hearing science metrics (HASQI, HASPI, PESQ, POLQA)
  • Signal processing fundamentals (DSP, beamforming, acoustic measurements)
  • Experience with human participant research and perceptual data collection
  • Background in computational hearing science or auditory cognitive neuroscience

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