Machine Learning Jobs
Machine learning jobs are open across technology, finance, healthcare, and autonomous systems, from new-grad engineer to principal and staff levels, with specializations in natural language processing, computer vision, and reinforcement learning. 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 Jobs by Experience Level
Top Cities Hiring Machine Learnings
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Find Machine Learning JobsMachine Learning Job Market
Who's Hiring
- Apple220
- JPMorganChase78
- Google60
- Amazon Web Services57
- General Motors53
Top Industries Hiring
- Technology & Software289
- Electronics & Hardware165
- Banking & Financial Services92
- Automotive60
- Science & Research32
What Employers Look For
The qualifications that appear most often in machine learning jobs.
- Proficiency in Python and at least one major ML framework such as PyTorch or TensorFlow
- Experience designing, training, and deploying machine learning models in production environments
- Strong foundation in statistics, linear algebra, and probability theory
- Familiarity with cloud platforms such as AWS, GCP, or Azure for ML workloads
- Experience with data pipelines, feature engineering, and model evaluation workflows
- Bachelor's or master's degree in computer science, statistics, mathematics, or a related field
Tips for Your Machine Learning Job Search
Tailor your resume to the stack
Machine learning job descriptions vary widely by framework. Swap generic terms like 'deep learning experience' for the exact tools listed, whether that's PyTorch, JAX, or Hugging Face Transformers. Recruiters and automated filters both scan for this match before a human reads your resume.
Showcase model performance with metrics
Hiring managers care about outcomes, not process. Replace 'built a recommendation model' with the actual lift it delivered, such as a reduction in latency or an improvement in click-through rate. Quantified results differentiate you from candidates who describe responsibilities instead of results.
Apply early to roles that fit
Migrate Mate lists machine learning openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Target roles by deployment context
A research-heavy role at a tech lab and a production machine learning role at a fintech company need different application angles. Lead with MLOps, CI/CD pipelines, and latency constraints when targeting production environments. Lead with publications and experimentation frameworks when applying to research-oriented teams.
Prepare a systems design answer for ML
Most machine learning interviews include a system design round specific to the role, like designing a fraud detection pipeline or a real-time ranking system. Practice articulating trade-offs between batch and streaming inference, model versioning, and feature store architecture before your first screen.
Negotiate on scope, not just base pay
Machine learning roles often have flexible scope around data ownership, compute budget, and research time. If an offer's compensation is fixed, ask about access to GPU clusters, conference budgets, or the ratio of research to production work. These factors affect your long-term career development as much as salary.
Machine Learning Jobs: Frequently Asked Questions
Which companies are hiring the most machine learnings?
The companies hiring the most machine learnings right now include Apple, JPMorganChase, and Google, 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 technology, financial services, and healthcare sectors.
How many machine learning jobs are remote?
About 56% of machine learning openings are fully remote or hybrid as of August 2026, making it one of the more flexible technical disciplines for location-independent work. Research engineering and NLP roles tend to have the highest remote availability, while applied roles tied to proprietary hardware or on-site data infrastructure are more often in-office.
How do you become a machine learning?
Start by building a strong foundation in Python programming, linear algebra, and probability. Work through core ML concepts using open datasets and document your projects in a public portfolio such as GitHub. Apply for junior or associate roles, internships, or research assistant positions that offer hands-on model development, and continue deepening your knowledge of deployment and MLOps as you gain experience.
Can you get a machine learning job with little or no experience?
Yes, entry-level machine learning roles exist and employers hiring for them prioritize demonstrated project work over years of experience. Build two or three end-to-end projects that show data preprocessing, model training, evaluation, and a basic deployment step. Contributing to open-source ML libraries and writing clearly about your technical decisions online also helps employers assess your skills when your resume is light.
What does the machine learning interview process look like?
Most machine learning interviews include an initial recruiter screen, a technical phone screen covering coding and ML fundamentals, a take-home or live machine learning case study, and a final loop with multiple rounds covering system design, model evaluation, and a cross-functional stakeholder interview. Research-focused roles often add a presentation of past work or a paper review discussion.
Where can I find and apply to machine learning jobs?
You can find and apply to machine learning jobs on Migrate Mate, which lists current openings from employers across the United States. Search the listings to find roles that match your experience and specialization, then apply directly to each one that fits.
See All 2,291+ Machine Learning Jobs
Find roles that match your experience and apply in just a few clicks.
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