Machine Learning Engineer Jobs
Machine Learning Engineer jobs are open across technology, finance, healthcare, and autonomous systems, from new-grad to staff and principal level, with specializations in natural language processing, computer vision, and recommendation systems. Find a role that fits from the openings below and apply directly.
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Are you passionate about search technologies and building knowledge experiences? The Answers, Knowledge, and Information team is at the forefront of revolutionizing how hundreds of millions of people use their devices to obtain information. We are a world-class team of machine learning engineers who collaborate closely with product, data science, and infrastructure teams to power and enhance features across Apple products, including Siri, Spotlight, Safari, Messages, and more. Our team operates in one of the most dynamic high-performance computing environments, managing petabytes of data and millions of queries per second. As a Senior Machine Learning Engineer, you play a critical role in developing world-class search and Q&A experiences for Apple customers using cutting-edge search technologies and large language models.
Description
As a member of our dynamic team, you will have the unique and rewarding opportunity to contribute to the development of upcoming products from Apple. Our team is responsible for delivering next-generation Search and Question Answering systems across Apple products, including Siri, Safari, Spotlight, and more. Therefore, we are seeking candidates with a deep understanding of large-scale search technology, machine learning fundamentals, applied machine learning experience, and strong software engineering skills. As Senior Machine Learning Engineer for the Search and Knowledge Quality team, you will be responsible for developing the ranking and retrieval technologies that power question answering and search across Apple products. In this role, you will collaborate with world-renowned experts in large-scale data management, machine learning systems, and knowledge extraction, driving advancements in question answering and search, as well as the underlying ranking and retrieval technologies. This is your opportunity to shape how people obtain information by leveraging your Search and applied machine learning expertise, along with robust software engineering skills.","responsibilities":"Analyze search retrieval, ranking and relevance requirements, issues and opportunities
Design, train, and deploy machine learning models to improve search relevance and ranking.
Define evaluation metrics and benchmarks for search quality.
Collaborate with multi-functional teams including: product, design, and data engineering.
Find opportunity and partner with various product teams across the company to apply search technology to new product areas and use cases.
Preferred Qualifications
Advance degree in Computer Science, Machine Learning, or a related field
10+ years of industry or academia experience in machine learning, with a focus on search, NLP, or recommender systems
Familiarity with NLP/ML tools and packages like Jax, TensorFlow, pyTorch, etc.
Experience working with transformer-based models (e.g., BERT, T5) in a search context
Prior industry experience on large scale search systems
Ability to quickly prototype ideas / solutions, perform critical analysis, and use creative approaches for solving complex problems
Minimum Qualifications
Bachelor’s in Computer Science, Machine Learning, or a related field
7+ years of industry or academia experience in machine learning, with a focus on search, NLP, or recommender systems
Strong programming skills in C/C++ or Python, and experience with ML frameworks
Proficient understanding of search algorithms and familiarity with evaluation metrics for search and information retrieval
Excellent communication and collaboration skills
Pay & Benefits
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 $184,700 and $324,800, 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.
Are you passionate about search technologies and building knowledge experiences? The Answers, Knowledge, and Information team is at the forefront of revolutionizing how hundreds of millions of people use their devices to obtain information. We are a world-class team of machine learning engineers who collaborate closely with product, data science, and infrastructure teams to power and enhance features across Apple products, including Siri, Spotlight, Safari, Messages, and more. Our team operates in one of the most dynamic high-performance computing environments, managing petabytes of data and millions of queries per second. As a Senior Machine Learning Engineer, you play a critical role in developing world-class search and Q&A experiences for Apple customers using cutting-edge search technologies and large language models.
Description
As a member of our dynamic team, you will have the unique and rewarding opportunity to contribute to the development of upcoming products from Apple. Our team is responsible for delivering next-generation Search and Question Answering systems across Apple products, including Siri, Safari, Spotlight, and more. Therefore, we are seeking candidates with a deep understanding of large-scale search technology, machine learning fundamentals, applied machine learning experience, and strong software engineering skills. As Senior Machine Learning Engineer for the Search and Knowledge Quality team, you will be responsible for developing the ranking and retrieval technologies that power question answering and search across Apple products. In this role, you will collaborate with world-renowned experts in large-scale data management, machine learning systems, and knowledge extraction, driving advancements in question answering and search, as well as the underlying ranking and retrieval technologies. This is your opportunity to shape how people obtain information by leveraging your Search and applied machine learning expertise, along with robust software engineering skills.","responsibilities":"Analyze search retrieval, ranking and relevance requirements, issues and opportunities
Design, train, and deploy machine learning models to improve search relevance and ranking.
Define evaluation metrics and benchmarks for search quality.
Collaborate with multi-functional teams including: product, design, and data engineering.
Find opportunity and partner with various product teams across the company to apply search technology to new product areas and use cases.
Preferred Qualifications
Advance degree in Computer Science, Machine Learning, or a related field
10+ years of industry or academia experience in machine learning, with a focus on search, NLP, or recommender systems
Familiarity with NLP/ML tools and packages like Jax, TensorFlow, pyTorch, etc.
Experience working with transformer-based models (e.g., BERT, T5) in a search context
Prior industry experience on large scale search systems
Ability to quickly prototype ideas / solutions, perform critical analysis, and use creative approaches for solving complex problems
Minimum Qualifications
Bachelor’s in Computer Science, Machine Learning, or a related field
7+ years of industry or academia experience in machine learning, with a focus on search, NLP, or recommender systems
Strong programming skills in C/C++ or Python, and experience with ML frameworks
Proficient understanding of search algorithms and familiarity with evaluation metrics for search and information retrieval
Excellent communication and collaboration skills
Pay & Benefits
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 $184,700 and $324,800, 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.
Machine Learning Engineer Jobs by Experience Level
Top Cities Hiring Machine Learning Engineers
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Find JobsMachine Learning Engineer Job Market
Who's Hiring
- Apple211
- Google48
- General Motors48
- Meta46
- Amazon Web Services46
Top Industries Hiring
- Technology & Software282
- Electronics & Hardware169
- Banking & Financial Services88
- Automotive61
- Consulting & Professional Services40
What Employers Look For
The qualifications that appear most often in machine learning engineer jobs.
- Proficiency in Python and ML frameworks such as PyTorch or TensorFlow
- Experience building and deploying models in cloud environments like AWS, GCP, or Azure
- Familiarity with MLOps tools including MLflow, Kubeflow, or SageMaker
- Strong foundation in statistics, linear algebra, and machine learning theory
- Bachelor's or master's degree in computer science, mathematics, or a related field
- Experience with large-scale data processing using Spark, SQL, or distributed systems
Tips for Your Machine Learning Engineer Job Search
Tailor your resume to deployment depth
Hiring managers distinguish candidates who trained models from those who shipped them to production. Explicitly note the serving infrastructure you used, the scale you operated at, and whether you owned monitoring and retraining pipelines, not just model accuracy metrics.
Build a GitHub portfolio that shows end-to-end work
Recruiters and engineers scan repositories for evidence you can move from raw data to a deployed artifact. Include notebooks, a training script, an inference endpoint, and a brief README explaining the problem you solved and what tradeoffs you made.
Apply early to roles that fit
Migrate Mate lists machine learning engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Filter openings by the ML stack you know best
Job postings for machine learning engineers vary sharply by framework, cloud platform, and data scale. Prioritize listings that name PyTorch, TensorFlow, JAX, or the specific cloud ML services you have hands-on experience with rather than applying broadly.
Prepare for system design questions alongside coding rounds
Most machine learning engineer interview loops include at least one session on designing scalable ML systems, such as a real-time feature store or an online ranking pipeline. Practice articulating latency budgets, retraining frequency, and data consistency tradeoffs out loud before your first screen.
Negotiate around compute budgets and research time
Beyond base compensation, ask about GPU or TPU access, experiment tracking tooling, and whether engineers are allocated time for internal research. These factors affect your ability to do meaningful work and are often negotiable, especially at mid-size companies.
Machine Learning Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most machine learning engineers?
The companies hiring the most machine learning engineers right now include Apple, Google, and General Motors, with the largest share of openings in California, Washington, and New York, based on current listings on Migrate Mate as of August 2026. Demand is concentrated in companies scaling generative AI, recommendation systems, and computer vision products.
How many machine learning engineer jobs are remote?
About 56% of machine learning engineer openings are fully remote or hybrid as of August 2026, making it one of the more flexible roles in software. Positions focused on NLP research and MLOps tooling tend to offer the highest share of remote flexibility, while roles tied to robotics or on-premise infrastructure typically require in-person work.
How do you become a machine learning engineer?
Start by building a strong foundation in Python, linear algebra, and statistics, then work through core ML concepts using publicly available datasets and open-source frameworks like PyTorch or scikit-learn. Add hands-on projects that go beyond notebooks to include model deployment and monitoring. A portfolio showing end-to-end ML systems carries more weight in hiring than coursework alone.
Can you get a machine learning engineer job with little or no experience?
Yes, entry-level machine learning engineer roles exist, particularly at startups and in companies building internal ML tooling. Focus your portfolio on projects that solve a real problem and deploy to a live endpoint. Contributing to open-source ML libraries, competing in public benchmarks, and demonstrating strong software engineering fundamentals will distinguish you from other early-career candidates.
What does the machine learning engineer interview process look like?
Most machine learning engineer loops include a recruiter screen, a technical phone interview covering Python and ML fundamentals, a take-home or live coding exercise, an ML system design session, and a final round with cross-functional team members. System design interviews often focus on topics like feature pipelines, model serving, and retraining strategies rather than abstract algorithms.
Where can I find and apply to machine learning engineer jobs?
You can find and apply to machine learning engineer jobs on Migrate Mate, which lists current openings from across the United States. Find roles that match your experience and specialization, then apply directly to each listing. The openings on this page are updated regularly so you can act on new postings as they appear.
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