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Audio Speech Machine Learning Jobs in Mars, PA (NOW HIRING)

Apple

Machine Learning Engineer

Pittsburgh, PA · On-site

As a Machine Learning Engineer in the Machine Intelligence Neural Design (MIND) team, you'll have ... Experience handling multimodal data including text, images, audio, and other sensors. Experience in ...

Apple

Machine Learning Engineer

Pittsburgh, PA

As a Machine Learning Engineer in the Machine Intelligence Neural Design (MIND) team, you'll have ... Experience handling multimodal data including text, images, audio, and other sensors. Experience in ...

Duolingo

Senior AI Research Engineer

Pittsburgh, PA · On-site

$101K - $139K/yr

The ideal candidate will have a proven track record as an AI research engineer, with experience across various machine learning techniques including large language models, speech models, benchmarking ...

Duolingo

Senior AI Research Engineer

Pittsburgh, PA · On-site

$197K - $266K/yr

The ideal candidate will have a proven track record as an AI research engineer, with experience across various machine learning techniques including large language models, speech models, benchmarking ...

Cmu

AI Security Software Engineer

Pittsburgh, PA · On-site +1

Familiarity with applied machine learning domains (e.g., natural language processing, computer vision, autonomy, audio analysis) * Experience and knowledge in cybersecurity best practices

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Audio Speech Machine Learning information

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 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 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 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 job categories do people searching Audio Speech Machine Learning jobs in Mars, PA look for?

The top searched job categories for Audio Speech Machine Learning jobs in Mars, PA are:

Audio Speech Machine Learning jobs near you
Infographic showing various Audio Speech Machine Learning job openings in Mars, PA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 80% In-person, and 20% Remote job distribution.

Machine Learning Engineer

Pittsburgh, PA • On-site

Apple
Computer and Electronic Product Manufacturing • 10K+ employees

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers

People enjoy working here

Good employer

Recommended by students

Learn more about Appleexternal

Full-time

Posted 20 days ago

Job description

As a Machine Learning Engineer in the Machine Intelligence Neural Design (MIND) team, you'll have the opportunity to be part of a leading ML innovation organization that develops a wide range of impactful Apple features. Within MIND, you'll engage in cutting-edge research in fields such as Foundation Models and Perception, and collaborate to create end products that have high impact on Apple users. This role places a strong emphasis on shipping ML-based features and products. You'll be involved in the entire end-to-end ML development pipeline, which encompasses creative approaches to dataset curation, model training, runtime inference integration, and on-device model optimizations. Our ideal team member is fearless in exploring new ideas and is willing to iterate on concepts. We value team members who can swiftly prototype and iterate, ultimately resulting in high-quality implementations.
Description
Our team seeks a self-driven machine learning engineer with strong experience in building ML training pipelines and developing production-quality inference infrastructure. In this role, you are expected to collaborate closely with ML researchers, SW/FW engineers, and Operation/Data engineers to advance different research and production efforts. Your role is to help deliver the needed pipeline for model development and evaluation, as well as build the production software to integrate these models and related functionality within Apple's software infrastructure. In addition, as part of the development process you are expected to build real-time demos and visualizations of sensing data streams and model predictions.
Minimum Qualifications
A PhD in computer science, computer engineering, or relevant Fields. Alternately, a BS or an MS + 3 to 5 years of ML engineering experience also qualifies.
Strong foundation in machine learning, and more specifically in LLM and multimodal foundation models.
Experience in building model training/eval pipelines in Python/PyTorch.
Experience in prototyping and developing software applications (preferably in Swift).
Experience with sensors and sensing systems.
Strong communication and presentation skills.
* Ability to work in a collaborative environment.
Preferred Qualifications
Proficient programming skills in Python and one of the deep learning toolkits such as JAX, PyTorch, or TensorFlow.
Experience in on-device ML model deployment and on-device optimization.
Experience handling multimodal data including text, images, audio, and other sensors.
Experience in developing production software.
Proficient in Swift, Objective-C, C++, or Go
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About Apple

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Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

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Benefits

Hours and flexibility

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