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Audio Speech Machine Learning Jobs in Boston, MA

We're looking for a Senior Machine Learning Engineer to help advance the state of voice ... Experience with audio models or speech systems (ASR, TTS, speaker modeling, etc.) * Experience with ...

Edge AI ML Engineer

Framingham, MA · On-site

$84K - $113K/yr

Strong experience developing and evaluating machine learning models, preferably for audio, speech, or other time-series sensor data. * Experience optimizing ML models for edge, embedded, or resource ...

Edge AI ML Engineer

Framingham, MA

$84K - $113K/yr

Strong experience developing and evaluating machine learning models, preferably for audio, speech, or other time-series sensor data. * Experience optimizing ML models for edge, embedded, or resource ...

Edge AI ML Engineer

Framingham, MA · On-site

$141 - $194/hr

Strong experience developing and evaluating machine learning models, preferably for audio, speech, or other time-series sensor data.Experience optimizing ML models for edge, embedded, or resource ...

New

DSP Engineer - Audio Tech

Framingham, MA · On-site

$147K - $171K/yr

Exposure to applied machine learning techniques for audio systems , such as ML-assisted noise reduction, speech enhancement, or audio classification. * Familiarity with Bluetooth audio systems and ...

DSP Engineer - Audio Tech

Framingham, MA · On-site

$147K - $171K/yr

Exposure to applied machine learning techniques for audio systems , such as ML-assisted noise reduction, speech enhancement, or audio classification. * Familiarity with Bluetooth audio systems and ...

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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 are popular job titles related to Audio Speech Machine Learning jobs in Boston, MA?

For Audio Speech Machine Learning jobs in Boston, MA, the most frequently searched job titles are:

What job categories do people searching Audio Speech Machine Learning jobs in Boston, MA look for?

The top searched job categories for Audio Speech Machine Learning jobs in Boston, MA are:

What cities near Boston, MA are hiring for Audio Speech Machine Learning jobs?

Cities near Boston, MA with the most Audio Speech Machine Learning job openings:

Infographic showing various Audio Speech Machine Learning job openings in Boston, MA as of August 2026, with employment types broken down into 89% Full Time, and 11% Part Time. Highlights an 89% In-person, and 11% Remote job distribution.

Machine Learning Applied Researcher - Speech, Vision and Audio

Cambridge, MA • On-site


Apple Inc.
Computer and Electronic Product Manufacturing • 10K+ employees

8.1

Company rating: 8.1 out of 10

Based on 678 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers

People enjoy working here

Good employer

Recommended by students


$132.10 - $199/hr

Other

Medical, Dental, Retirement

Re-posted 11 days ago


Job description

Machine Learning Applied Researcher - Speech, Vision and Audio

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, smart 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 passion for innovation that goes into our products also applies to our practices strengthening our commitment to leave the world better than we found it. Join us to help deliver the next groundbreaking Apple product. Do you love working on challenges that no one has solved yet? As a member of our dynamic group, you will have the unique and rewarding opportunity to craft upcoming products that will delight and inspire millions of Apple’s customers every single day.

Description

We are looking for a talented and experienced applied ML researcher who can both research new capabilities and develop frontier models using cutting‑edge methods. In this role, you will take on high‑risk, high‑reward challenges – researching, designing, and improving state‑of-the‑art deep learning models trained on unique data, implementing novel machine learning algorithms, and developing solutions to problems that don't have obvious answers. Your scope will encompass various ML subfields and modalities, combining ideas from different fields to solve unique challenges and deliver solutions adopted broadly across teams.

Responsibilities
  • Research and develop cutting‑edge deep learning models and algorithms, leveraging multiple data modalities (e.g., vision, audio, sensor, text).
  • Design and implement novel neural network architectures solving unique challenges in the field of ASR.
  • Navigate ambiguous problem spaces – formulate hypotheses, run experiments, learn from negative results, and iterate toward solutions.
  • Improve model performance while maintaining awareness of deployment constraints such as latency, memory, and compute.
  • Collaborate across teams, synthesizing approaches from different fields into solutions that work with and benefit the entire organization.
  • Communicate findings clearly to stakeholders and team members.
  • Stay current with scientific literature on frontier ML methods and identify opportunities to apply new ideas.
Minimum Qualifications
  • BS in Computer Science, Electrical Engineering, or a related field – or equivalent practical experience.
  • Experience in academic or industry research.
  • Experience working with Pytorch.
Preferred Qualifications
  • MS or PhD in Computer Science, Electrical Engineering, or a related field.
  • Strong foundation in deep learning theory and hands‑on experience training large‑scale models.
  • Deep knowledge in one or more of: self‑supervised learning, synthetic data generation, large language model training, or automatic speech recognition.
  • Experience working with multimodal data (e.g., images, audio, time‑series, or sensor fusion).
  • Strong analytical and problem‑solving skills; ability to translate research ideas into production‑quality code.
  • Resilience and persistence – comfort with experimentation cycles where many attempts fail before one succeeds.
  • Publication record at top‑tier ML venues (NeurIPS, ICML, ICLR, Interspeech, ICASSP, etc.).
  • Multidisciplinary background spanning fields such as neuroscience, physics, signal processing, or mathematics. Experience collaborating with distributed teams across time zones.

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $132,100 and $199,000, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

Learn about accessibility in Apple’s workplace

Learn about reasonable accommodations for job applicants

Apple accepts applications to this posting on an ongoing basis.

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About Apple

Sourced by ZipRecruiter

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


What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

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