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Speech Processing Jobs (NOW HIRING)

Zencastr

Senior Machine Learning Engineer (Remote)

New York, NY · On-site +1

$114K - $157K/yr

Experience with modern speech processing frameworks * Good dev ops experience * Advanced DSP experience * MongoDB or SQL experience * Experience with unit, integration, and load testing * Experience ...

Mastech Digital

Be Seen First

Text and Speech Analyst

Tampa, FL · Remote

$80K - $110K/yr

· The Text and Speech Analyst is responsible for analyzing, interpreting, and evaluating language ... The ideal candidate will have a strong background in AI, natural language processing, and neural ...

Sanas

Senior Software Engineer

Palo Alto, CA · On-site

$144K - $190K/yr

Required : • Bachelor's in Computer Science, Electrical Engineering, or a related field with a focus on Machine Learning, Deep Learning, Natural Language Processing, or Speech Processing and 2 ...

The Walt Disney Company

Sr Staff R&D Engineer

Nicasio, CA · On-site

$206K - $276K/yr

This senior-level role is central to advancing our next-generation soundtrack platform, with a focus on speech processing, style transfer, upmixing, source separation, and generative audio synthesis.

Kubikware

AI Engineer (Latam, Remote)

Miami, FL · Remote

Open AI Whisper API for transcription and speech processing * Claude AI and LLM integrations * n8n for workflow automation and orchestration * Replit for rapid app/web development and prototyping

Speech on Wheels LLC

Speech Therapist

Fallbrook, CA

$60 - $90/hr

... in the process of accumulating the supervised experience required for certification. Must be ... Speech on Wheels LLC is an Equal Opportunity Employer and encourages applicants from diverse ...

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Speech Processing information

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How much do speech processing jobs pay per hour?

As of Jul 2, 2026, the average hourly pay for speech processing in the United States is $41.32, according to ZipRecruiter salary data. Most workers in this role earn between $35.10 and $45.91 per hour, depending on experience, location, and employer.

What is the difference between Speech Processing vs Speech Recognition?

AspectSpeech ProcessingSpeech Recognition
DefinitionBroad field involving analysis, modification, and synthesis of speech signalsSubfield focused on converting spoken language into text
Skills & CertificationsSignal processing, audio engineering, programming; certifications like DSP or audio engineeringMachine learning, NLP, programming; certifications in AI or speech technology
Work EnvironmentResearch labs, tech companies, audio hardware firmsSoftware development, AI companies, voice assistant firms
Industry UsageTelecommunications, audio processing, speech synthesisVirtual assistants, transcription services, voice command systems

Speech Processing is a broad field encompassing various aspects of speech signal analysis and synthesis, while Speech Recognition specifically focuses on converting spoken words into written text. Both roles often require similar technical skills and certifications, but their applications differ across industries and job functions.

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

To excel as a Speech Processing Engineer, you need strong programming skills, a background in digital signal processing, and a degree in computer science, electrical engineering, or a related field. Experience with tools like Python, MATLAB, and libraries such as Kaldi or TensorFlow, as well as knowledge of machine learning frameworks, is typically required. Strong problem-solving, analytical thinking, and clear communication skills help in designing effective solutions and collaborating with cross-functional teams. These skills ensure the development of accurate, efficient speech recognition and synthesis systems that meet user and business needs.

What is speech processing?

Speech processing is a field within computer science and electrical engineering focused on analyzing, interpreting, and manipulating human speech signals. It includes tasks such as speech recognition, speaker identification, speech synthesis, and speech enhancement. These technologies enable computers and devices to understand spoken language, convert speech to text, or generate natural-sounding synthetic voices. Speech processing is used in virtual assistants, voice-controlled devices, and accessibility tools.

What are some common challenges faced by professionals in Speech Processing roles, and how can they be addressed?

Professionals in Speech Processing often encounter challenges related to handling diverse accents, background noise, and varying speech patterns, which can impact the accuracy of speech recognition systems. To address these issues, teams frequently collaborate with linguists and data scientists to refine algorithms, utilize large and diverse datasets, and implement advanced noise reduction techniques. Staying updated with the latest research and regularly evaluating system performance are also essential practices to ensure robust and adaptable speech processing solutions.
More about Speech Processing jobs
What cities are hiring for Speech Processing jobs? Cities with the most Speech Processing job openings:
What states have the most Speech Processing jobs? States with the most job openings for Speech Processing jobs include:
What job categories do people searching Speech Processing jobs look for? The top searched job categories for Speech Processing jobs are:
Speech Processing jobs near you
Text and Speech Analyst

Text and Speech Analyst

Expert Technology Services

Tampa, FL • On-site

Contractor

Posted 10 days ago

Job description

Please Note: As of July 22, 2021, our team will require that all candidate submissions include a LinkedIn profile. Please do not submit any candidates that do not have a LinkedIn.

 

URGENT REQUIREMENT

 

Looking for candidates regarding the following:

POSITION

Text & Speech Analyst
INDUSTRY
 

LOCATION

REMOTE

 
Please Target Candidates in the following States :

Alabama Arizona Arkansas Colorado Connecticut Delaware Florida Georgia Idaho Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Michigan Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Mexico North Carolina North Dakota Ohio Oklahoma Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas Utah Vermont Virginia West Virginia Wisconsin Wyoming

 

DURATION

6+ month
 

INTERVIEW TYPE

Video

VISA TYPE

NO SPONSORSHIP AVAILABLE

REQUIRED SKILLS

Must-Haves:
  • Strong experience with ASR / speech recognition (Wav2Vec, DeepSpeech) + classical speech processing (HMM, GMM, ANN, language modeling)
  • Advanced programming in Python (required) + experience with AI/ML frameworks (TensorFlow, PyTorch, Keras)
  • Hands-on deep learning for speech/NLP (CNNs, CTC, Transformer models like BERT/GPT)
  • Cloud experience deploying AI solutions (Azure preferred; AWS/GCP acceptable)
  • Solid NLP + data management experience (data preprocessing, augmentation, synthetic data, labeling)
Preferred:
  • Experience with Azure AI Services, Azure ML, or Databricks/Snowflake (AI capabilities)
  • Exposure to open-source speech models (Kaldi, Whisper)
  • MLOps experience (model deployment, monitoring, lifecycle management)
  • Knowledge of data governance, security, and compliance practices
  • Familiarity with data visualization/reporting tools (Power BI, Webfocus)
  •  

Required Skills : * Working knowledge of ASR engines using frameworks like Wav2vec or Deep Speech * Working knowledge of Azure AI Services * Advanced programming knowledge, including mastery of programming languages such as Python, C , Java, and especially AI-centric libraries like TensorFlow, PyTorch, and Keras * Cloud computing and knowledge for deploying and managing AI applications on cloud platforms like AWS, Google Cloud, or Microsoft Azure * Expertise in classical speech processing methodologies like hidden Markov models (HMMs), Gaussian mixture models (GMMs), Artificial neural networks (ANNs), Language modeling, etc. * Functional knowledge of Snowflake and/or Databricks for AI capabilities and data management * Hands on experience on current deep learning (DL) techniques like Convolutional neural networks (CNNs), connectionist temporal classification (CTC) used for speech processing * Exposure to open-source models such as Kaldi or OpenAI Whisper * Data management knowledge, including data pre-processing, augmentation, and generation of synthetic data, including the cleaning, labeling, and augmenting of data to train and improve AI models * Proficiency in Transformer Models like BERT-base. ELMo, ULM-FIT * Experience with AI tools, such as MS Azure ML, Databricks AI, Snowflake CortexAI, Dataiku

Basic Qualification :

Additional Skills :

Background Check : No

Drug Screen : No


Rank :A3
Requested Date :2026-06-22