Mid Level Machine Learning Engineering Manager Jobs
Mid level machine learning engineering manager jobs go to professionals ready to own model development pipelines end to end, guide junior engineers, and make architectural decisions with limited oversight. Openings are concentrated across Technology & Software, Electronics & Hardware, and Banking & Financial Services, with a mix of on-site, remote, and hybrid settings, and employers like Apple, Cisco, and Pinterest hiring at this level now.
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Wonder how Apple's Media Products show relevant search results and recommendations across Apple's media offerings - including App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books? Come join us! Design, build, and deploy recommendation models that personalize the App Store for billions of users worldwide! See your work touch the lives of billions of Apple users worldwide. The Apple Services Engineering team is one of the most exciting examples of Apple's long-held passion for combining art and technology. We are the people who power the App Store, Apple TV, Apple Music, Apple Podcasts, Games and Apple Fitness+. And we do it on a massive scale, meeting Apple's high expectations with high performance, to deliver a huge variety of entertainment in over 35 languages to more than 150 countries. Our researchers and engineers build secure, end-to-end solutions powered by machine learning. Thanks to Apple's unique integration of hardware, software, and services, designers, scientists and engineers here partner to get behind a single unified vision. That vision always includes a deep commitment to strengthening Apple's privacy policy, one of Apple's core values. Although services are a bigger part of Apple's business than ever before, these teams remain small, flexible, and multi-functional, offering greater exposure to the array of opportunities here.
Description
We are looking for an exceptional Machine Learning Engineer to help us design, build, and ship recommendation models that power personalization across the App Store. With your expertise, we want to develop novel solutions to power personalized experiences across the App Store that enrich the lives of our customers. You will have the incredible opportunity to partner with researchers to see cutting-edge AI models deployed reliably at Apple's truly incredible global scale.
Minimum Qualifications
- Bachelor's and Master's in a quantitative field, including Computer Science, Mathematics, Statistics, Physics, etc.
- 3+ years of relevant work experience.
- Hands-on experience with production-level recommender systems.
- Deep knowledge of recommendation systems, design patterns and tools, with particular depth in deep-learning architectures and multi-task modeling.
- Proven track record of shipping recommendation models to production at scale, with a strong understanding of the constraints of serving billions of users.
- Knowledge of modern recommendation architectures across retrieval and ranking, multi-task learning, sequence and transformer-based models, generative recommenders, and multi-objective optimization.
- Proven grasp of the open-source Python ML/AI tech stack, including TensorFlow, PyTorch, scikit-learn, numpy-scipy-pandas.
- Familiarity with big data technologies and distributed computing (e.g., Spark, Hadoop, Kafka).
- Familiarity with using LLM-powered tools (coding and research assistants) to accelerate day-to-day engineering and research workflows.
- Strong written & oral communication skills.
Preferred Qualifications
- PhD in a quantitative field, including Computer Science, Mathematics, Statistics, Physics, etc.
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 $142,300 and $263,300, 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.
Wonder how Apple's Media Products show relevant search results and recommendations across Apple's media offerings - including App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books? Come join us! Design, build, and deploy recommendation models that personalize the App Store for billions of users worldwide! See your work touch the lives of billions of Apple users worldwide. The Apple Services Engineering team is one of the most exciting examples of Apple's long-held passion for combining art and technology. We are the people who power the App Store, Apple TV, Apple Music, Apple Podcasts, Games and Apple Fitness+. And we do it on a massive scale, meeting Apple's high expectations with high performance, to deliver a huge variety of entertainment in over 35 languages to more than 150 countries. Our researchers and engineers build secure, end-to-end solutions powered by machine learning. Thanks to Apple's unique integration of hardware, software, and services, designers, scientists and engineers here partner to get behind a single unified vision. That vision always includes a deep commitment to strengthening Apple's privacy policy, one of Apple's core values. Although services are a bigger part of Apple's business than ever before, these teams remain small, flexible, and multi-functional, offering greater exposure to the array of opportunities here.
Description
We are looking for an exceptional Machine Learning Engineer to help us design, build, and ship recommendation models that power personalization across the App Store. With your expertise, we want to develop novel solutions to power personalized experiences across the App Store that enrich the lives of our customers. You will have the incredible opportunity to partner with researchers to see cutting-edge AI models deployed reliably at Apple's truly incredible global scale.
Minimum Qualifications
- Bachelor's and Master's in a quantitative field, including Computer Science, Mathematics, Statistics, Physics, etc.
- 3+ years of relevant work experience.
- Hands-on experience with production-level recommender systems.
- Deep knowledge of recommendation systems, design patterns and tools, with particular depth in deep-learning architectures and multi-task modeling.
- Proven track record of shipping recommendation models to production at scale, with a strong understanding of the constraints of serving billions of users.
- Knowledge of modern recommendation architectures across retrieval and ranking, multi-task learning, sequence and transformer-based models, generative recommenders, and multi-objective optimization.
- Proven grasp of the open-source Python ML/AI tech stack, including TensorFlow, PyTorch, scikit-learn, numpy-scipy-pandas.
- Familiarity with big data technologies and distributed computing (e.g., Spark, Hadoop, Kafka).
- Familiarity with using LLM-powered tools (coding and research assistants) to accelerate day-to-day engineering and research workflows.
- Strong written & oral communication skills.
Preferred Qualifications
- PhD in a quantitative field, including Computer Science, Mathematics, Statistics, Physics, etc.
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 $142,300 and $263,300, 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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Mid Level Machine Learning Engineering Manager Jobs: Frequently Asked Questions
How do I get a mid level machine learning engineering manager job?
Position yourself by highlighting ownership, not just contribution. Emphasize projects where you drove the full ML lifecycle, from problem framing to deployment, and any experience coordinating across teams or reviewing others' work. Tailor your resume to show technical depth in your specialization, whether that is computer vision, NLP, or recommendation systems, alongside evidence of independent judgment and cross-functional collaboration.
Which companies hire mid level machine learning engineering managers?
Companies hiring mid level machine learning engineering managers right now include Apple, Cisco, and Pinterest, based on current listings on Migrate Mate as of November 2026. At this level, hiring comes from a range of employers, including tech-forward enterprises, well-funded startups scaling their AI teams, and large organizations building out dedicated machine learning practices.
Are there remote mid level machine learning engineering manager jobs?
Yes, though availability varies by employer and seniority expectations. About 50% of mid level machine learning engineering manager openings are remote or hybrid as of November 2026, reflecting strong demand for this role outside traditional tech hubs. Many employers at this level favor hybrid arrangements that keep managers connected to engineering teams and stakeholders.
How do I move up to a mid level machine learning engineering manager role?
The path runs through depth and demonstrated ownership. Early in your career, focus on mastering the ML stack your team uses, then push to lead a project or feature from scoping through production. Building a track of measurable outcomes, such as model accuracy improvements or reduced inference latency, combined with informal mentorship of newer teammates, is what hiring managers look for when evaluating mid level readiness.
Which industries hire the most mid level machine learning engineering managers?
Mid Level machine learning engineering manager roles concentrate in Technology & Software, Electronics & Hardware, and Banking & Financial Services, based on current listings on Migrate Mate as of November 2026. These sectors invest heavily in predictive modeling, personalization, and automation at scale, creating sustained demand for managers who can bridge hands-on ML work with team coordination and product delivery.