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Apple Machine Learning Engineer Jobs in Massachusetts

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 ...

Machine Learning Engineer

Boston, MA · On-site

$136.32 - $225.09/hr

## Machine Learning EngineerApplyremote type: Hybridlocations: Bostontime type: Full timeposted on ... Apply standard software engineering practices, including version control, code reviews, and ...

The Alexa AI team is looking for a passionate, talented, and inventive Machine Learning Engineer with a strong machine learning background, to build capabilities such as fine tuning, distillation ...

Xometry is looking for a Staff Machine Learning Engineer to join our growing AI/ML team. This is a senior individual contributor role with broad technical scope and meaningful organizational impact.

Opportunity Overview As a Machine Learning Engineer, you will design, develop, and deploy applied AI solutions with a good knowledge on graph machine learning, reinforcement learning, and ...

Senior Machine Learning Engineer

Andover, MA · On-site

$105K - $145K/yr

Rockstar Games is on the lookout for a skilled Senior Machine Learning Engineer with strong software development skills who is passionate about games, big data and Machine Learning to join a team ...

Xometry is looking for a Staff Machine Learning Engineer to join our growing AI/ML team. This is a senior individual contributor role with broad technical scope and meaningful organizational impact.

Lead Machine Learning Engineer

Cambridge, MA · On-site

$112K - $147K/yr

Lead Machine Learning Engineer At Capital One, we are changing banking for good by creating responsible and reliable AI-powered systems. Our investments in technology infrastructure and world-class ...

Lead Machine Learning Engineer

Cambridge, MA · On-site

$112K - $147K/yr

Lead Machine Learning Engineer At Capital One, we are changing banking for good by creating responsible and reliable AI-powered systems. Our investments in technology infrastructure and world-class ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

Showing results 41-60

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

Bespoke Labs

Cambridge, MA • On-site

Full-time

Re-posted 23 days ago


Job description

About Us

We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.

We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.

What You'll Be Working On

You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments — and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.

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 preferred; familiar with training loops, optimizers, mixed precision)

Hands-on experience with LLM post-training — SFT, RLHF, PPO, DPO, or reward model training — and understanding of how training data quality affects model behavior

Familiarity with RL frameworks (Gymnasium, dm_env) and the ability to design or modify reward functions for agent training objectives

Experience running experiments at scale on cloud or HPC (AWS, GCP, SLURM, or Ray)

Solid understanding of evaluation methodology — held-out sets, benchmark design, avoiding train/eval contamination