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Apple Machine Learning Engineer Jobs in Massachusetts

The Core for Computational Biomedicine (CCB) in the Department of Biomedical Informatics (DBMI) at Harvard Medical School (HMS) is looking for a Machine Learning Engineer with advanced expertise to ...

Machine Learning Engineer

Woburn, MA · On-site

$115K - $140K/yr

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML models into production systems that solve critical national security problems. Working as part of a ...

Software Machine Learning Engineer

Reading, MA · On-site

$116.50 - $186.40/hr

Software Machine Learning Engineer Location: North Reading, MA, US Our Purpose TERADYNE, where experience meets innovation and driving excellence in every connection. We are fueled by creativity and ...

Machine Learning Engineer

Woburn, MA · On-site

$115K - $140K/yr

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML models into production systems that solve critical national security problems. Working as part of a ...

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML models into production systems that solve critical national security problems. Working as part of a ...

Machine Learning Engineer

Woburn, MA · On-site

$115 - $140/hr

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML models into production systems that solve critical national security problems. Working as part of a ...

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML models into production systems that solve critical national security problems. Working as part of a ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Showing results 21-40

Apple Machine Learning Engineer information

See Massachusetts salary details

$34.4K

$140.6K

$211.3K

How much do apple machine learning engineer jobs pay per year?

As of Aug 10, 2026, the average yearly pay for apple machine learning engineer in Massachusetts is $140,632.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,800.00 and $169,300.00 per year, depending on experience, location, and employer.

Is machine learning a high paying job?

Machine learning engineers typically earn high salaries due to the specialized skills required, such as proficiency in programming, data analysis, and model development. Salaries vary based on experience, location, and industry, but overall, it is considered a well-compensated field within technology roles.

What collaboration opportunities can an Apple machine learning engineer expect when working on cross-functional projects?

As an Apple Machine Learning Engineer, you will frequently collaborate with cross-functional teams including software engineers, product managers, and user experience designers. This collaboration is essential for integrating machine learning solutions seamlessly into Apple’s products and services. You can expect to participate in regular meetings to align on project goals, share technical insights, and troubleshoot challenges together. Such teamwork not only enhances product quality but also offers valuable opportunities for professional growth and skill development within Apple’s innovative environment.

What does an Apple machine learning engineer do?

An Apple Machine Learning Engineer designs, develops, and implements machine learning models and algorithms that power Apple's products and services. They work with large datasets, collaborate with software and hardware teams, and contribute to features such as Siri, image recognition, and personalized recommendations. Their role involves researching new techniques, optimizing models for performance and efficiency, and ensuring privacy and security standards are maintained.

What is the difference between Apple Machine Learning Engineer vs Apple Data Scientist?

AspectApple Machine Learning EngineerApple Data Scientist
Required CredentialsBachelor's or Master's in CS, ML, or related fields; experience with ML frameworksBachelor's or Master's in CS, Statistics, or related fields; strong analytical skills
Work EnvironmentDeveloping ML models, algorithms, deploying on Apple devicesAnalyzing data, building insights, supporting product decisions
Employer & Industry UsageTech industry, Apple-specific projects, hardware/software integrationTech industry, product analytics, user behavior insights

Apple Machine Learning Engineers focus on developing and deploying ML models within Apple's ecosystem, while Apple Data Scientists analyze data to inform product decisions. Both roles require strong technical skills, but ML Engineers are more involved in model creation and deployment, whereas Data Scientists focus on data analysis and insights.

What are the key skills and qualifications needed to thrive as an Apple machine learning engineer, and why are they important?

To thrive as an Apple Machine Learning Engineer, you need a strong background in computer science, mathematics, and statistics, typically with experience in machine learning algorithms and a relevant degree. Expertise in programming languages such as Python or Swift, familiarity with frameworks like TensorFlow or PyTorch, and knowledge of Apple's Core ML are commonly required. Strong problem-solving abilities, creativity, and effective communication help you collaborate across teams and translate complex ideas. These skills ensure innovative, scalable, and user-centric machine learning solutions that align with Apple's high standards.

How do I get into Apple as an Apple Machine Learning Engineer?

To become an Apple Machine Learning Engineer, candidates typically need a strong background in computer science, machine learning, or related fields, with proficiency in programming languages like Python and experience with frameworks such as TensorFlow or PyTorch. Relevant skills include data analysis, model development, and familiarity with Apple's ecosystem, often supported by a bachelor's or master's degree and a strong portfolio of projects or research. Applying through Apple's careers website and demonstrating technical expertise during interviews are essential steps.
What job categories do people searching Apple Machine Learning Engineer jobs in Massachusetts look for? The top searched job categories for Apple Machine Learning Engineer jobs in Massachusetts are:
What cities in Massachusetts are hiring for Apple Machine Learning Engineer jobs? Cities in Massachusetts with the most Apple Machine Learning Engineer job openings:
Infographic showing various Apple Machine Learning Engineer job openings in Massachusetts as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $140,632 per year, or $67.6 per hour.

Machine Learning Engineer

Harvard University

Boston, MA • On-site, Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 12 days ago


Harvard University rating

8.5

Company rating: 8.5 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

80th of 617 rated colleges and universities


Job description

Company Description

By working at Harvard University, you join a vibrant community that advances Harvard's world-changing mission in meaningful ways, inspires innovation and collaboration, and builds skills and expertise. We are dedicated to creating a diverse and welcoming environment where everyone can thrive.

Why join Harvard Medical School?

Harvard Medical School's mission is to nurture a diverse, inclusive community dedicated to alleviating suffering and improving health and well-being for all through excellence in teaching and learning, discovery and scholarship, and service and leadership.

You'll be at the heart of biomedical discovery, education, and innovation, working alongside world-renowned faculty and a community dedicated to improving human health. This is more than a job - it's an opportunity to shape the future of medicine.

Job Description

The Core for Computational Biomedicine (CCB) in the Department of Biomedical Informatics (DBMI) at Harvard Medical School (HMS) is looking for a Machine Learning Engineer with advanced expertise to lead development of large language models (LLMs) to advance CCB's mission to leverage data and computation to transform research and education, and to improve health outcomes. CCB provides computational and analytic resources to advance scientific discovery within HMS through its multi-disciplinary team of computational and quantitative scientists who work on collaborative projects both within the center and with members of the HMS community. The selected candidate will play a pivotal role in advancing the center's mission to harness the power of computational techniques in the field of medicine. By developing medical LLMs, the engineer will contribute to educating the next generation of medical students and enhancing clinical decision-making processes.
Key Responsibilities:

  • Develop, implement, and optimize medical large language models tailored to the needs of medical education and clinical decision support.
  • Collaborate with interdisciplinary teams comprising biologists, clinicians, and data scientists to understand domain-specific requirements and translate them into computational solutions.
  • Stay updated with the latest advancements in deep learning and machine learning to ensure the models developed are state-of-the-art.
  • Develop infrastructures for data transformation and ingestion.
  • Build AI models that make predictions based on large quantities of data.
  • Explain the usefulness of the AI models created to stakeholders.
  • Transform machine learning models into APIs to interact with other applications.
  • Use expert knowledge to lead research AI and data science projects. 
Qualifications

Basic Qualifications:

  • Minimum of seven years' post-secondary education or relevant work experience.


Additional Qualifications and Skills:

  • A Master's or PhD in Computer Science, Computational Biology, or a related field is strongly preferred.
  • Minimum of 3 years of hands-on experience in developing complex deep learning solutions to tackle scientific challenges.
  • Proficiency with the Python deep learning software stack, particularly expertise in PyTorch, Numpy, and related packages.
  • Experience handling and processing large and diverse datasets, especially medical texts, journals, or electronic health records.
  • Ability to collaborate effectively with non-technical stakeholders, such as doctors and medical researchers.
  • Experience with experiment tracking and project management tools, notably frameworks like Weights & Biases.
  • Prior experience in fine-tuning large language models for specific tasks.
  • Demonstrated experience in optimizing deep learning models for better performance and efficiency.
  • Understanding of biology and/or medicine to bridge the gap between pure machine learning and its applications in the medical field.
  • A track record of publications in technical conferences or journals.
Additional Information
  • Standard Hours/Schedule: 35 hours per week
  • Visa Sponsorship Information: Harvard University is unable to provide visa sponsorship for this position.
  • Pre-Employment Screening: Identity, Education, Criminal
  • Other Information: Please note that we are currently conducting a majority of interviews and onboarding remotely and virtually. We appreciate your understanding.
  • Staying Informed About Your Application: Due to the high volume of applications, we may not always be able to reach out right away, but you can track your status anytime through the Careers@Harvard portal. 

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Work Format Details

This position has been determined by school or unit leaders that some of the duties and responsibilities can be effectively performed at a non-Harvard location. The work schedule and location will be set by the department at its discretion and based upon operational needs. When not working at a Harvard or Harvard-designated location, employees in hybrid positions must work in a Harvard registered state in compliance with the University's Policy on Employment Outside of Massachusetts. Additional details will be discussed during the interview process. Certain visa types and funding sources may limit work location. Individuals must meet work location sponsorship requirements prior to employment.

Salary Grade and Ranges

This position is salary grade level 060. Please visit Harvard's Salary Ranges to view the corresponding salary range and related information. 

Benefits

Harvard offers a comprehensive benefits package that is designed to support a healthy work-life balance and your physical, mental and financial wellbeing. Because here, you are what matters. Our benefits include, but are not limited to: 

  • Generous paid time off including parental leave 
  • Medical, dental, and vision health insurance coverage starting on day one 
  • Retirement plans with university contributions 
  • Wellbeing and mental health resources 
  • Support for families and caregivers 
  • Professional development opportunities including tuition assistance and reimbursement 
  • Commuter benefits, discounts and campus perks 

Learn more about these and additional benefits on our Benefits & Wellbeing Page. 

EEO/Non-Discrimination Commitment Statement

Harvard University is committed to equal opportunity and non-discrimination. We seek talent from all parts of society and the world, and we strive to ensure everyone at Harvard thrives. Our differences help our community advance Harvard's academic purposes.

Harvard has an equal employment opportunity policy that outlines our commitment to prohibiting discrimination on the basis of race, ethnicity, color, national origin, sex, sexual orientation, gender identity, veteran status, religion, disability, or any other characteristic protected by law or identified in the university's non-discrimination policy. Harvard's equal employment opportunity policy and non-discrimination policy help all community members participate fully in work and campus life free from harassment and discrimination.


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