Efficiency Engineer Jobs for OPT Students
Efficiency Engineer jobs are a strong fit for F-1 OPT students with backgrounds in industrial engineering, operations research, or systems engineering. Most roles qualify as STEM OPT, giving you up to 36 months of work authorization. Employers in manufacturing, logistics, and consulting actively hire for this title.
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Are you passionate about Generative AI and excited to work on groundbreaking modeling technologies that will enrich the lives of billions? The Intelligence System Experience (ISE) team within Apple’s software organization is a multidisciplinary group operating at the intersection of Multimodal Foundation Models, Efficient and Scalable ML Infrastructure, and Personalized Intelligent Experiences. As a senior machine learning engineer on our team, you will design software systems and algorithms that enable performant, scalable training and inference for Apple’s AI-driven experiences across both on-device and server environments. This role also includes opportunities to open source your work. Join our team of highly skilled, impact-focused engineers!
Description
We’re seeking strong senior machine learning engineers to help build next-generation tools for large-scale deep learning. You’ll join a team focused on accelerating training and inference speed, improving scalability, and advancing Apple’s centralized ML platform. Candidates should bring polished coding skills and a passion for machine learning and computational science. We offer a respectful work environment, flexible responsibilities, and access to world-class experts and growth opportunities.
In this role, you will develop core components for our scalable ML platform, push the limits of existing training technologies, and create new techniques to overcome system constraints. Your work will be deployed on high-impact tasks across teams building Apple Intelligence products, with opportunities to open-source your contributions. We are especially looking for a PyTorch-focused ML efficiency expert to optimize training and inference performance, improve distributed training throughput, and drive system-level efficiency for large-scale models. If you have deep experience with PyTorch internals and high-performance ML infrastructure, we’d love to hear from you.
Minimum Qualifications
- PhD or Master's degree in the area of Computer Science, or equivalent years of industry experience
- 3+ years working with AI/ML technologies in production or research settings
- Strong Python programming skills
- Understanding software design principles, and algorithms
- Experience with deep learning frameworks, such as PyTorch
- Experience building large-scale distributed systems
- Familiarity with parallelization algorithms for large model training
- Familiarity with recent developments in foundation model architectures
Preferred Qualifications
- Experience developing model parallel and data parallel training solutions and other training optimizations
- Experience with parallel training libraries such as torch.distributed, DeepSpeed, or FairScale
- Experience with CUDA-level optimization
- Experience building ML models targeting Apple Silicon
- Experience building large-scale deep learning infrastructure or platforms for distributed model training
- Publication record at Machine Learning conferences such as MLSys, NeurIPS, etc.
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.
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 $171,600 and $302,200, 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 Generative AI and excited to work on groundbreaking modeling technologies that will enrich the lives of billions? The Intelligence System Experience (ISE) team within Apple’s software organization is a multidisciplinary group operating at the intersection of Multimodal Foundation Models, Efficient and Scalable ML Infrastructure, and Personalized Intelligent Experiences. As a senior machine learning engineer on our team, you will design software systems and algorithms that enable performant, scalable training and inference for Apple’s AI-driven experiences across both on-device and server environments. This role also includes opportunities to open source your work. Join our team of highly skilled, impact-focused engineers!
Description
We’re seeking strong senior machine learning engineers to help build next-generation tools for large-scale deep learning. You’ll join a team focused on accelerating training and inference speed, improving scalability, and advancing Apple’s centralized ML platform. Candidates should bring polished coding skills and a passion for machine learning and computational science. We offer a respectful work environment, flexible responsibilities, and access to world-class experts and growth opportunities.
In this role, you will develop core components for our scalable ML platform, push the limits of existing training technologies, and create new techniques to overcome system constraints. Your work will be deployed on high-impact tasks across teams building Apple Intelligence products, with opportunities to open-source your contributions. We are especially looking for a PyTorch-focused ML efficiency expert to optimize training and inference performance, improve distributed training throughput, and drive system-level efficiency for large-scale models. If you have deep experience with PyTorch internals and high-performance ML infrastructure, we’d love to hear from you.
Minimum Qualifications
- PhD or Master's degree in the area of Computer Science, or equivalent years of industry experience
- 3+ years working with AI/ML technologies in production or research settings
- Strong Python programming skills
- Understanding software design principles, and algorithms
- Experience with deep learning frameworks, such as PyTorch
- Experience building large-scale distributed systems
- Familiarity with parallelization algorithms for large model training
- Familiarity with recent developments in foundation model architectures
Preferred Qualifications
- Experience developing model parallel and data parallel training solutions and other training optimizations
- Experience with parallel training libraries such as torch.distributed, DeepSpeed, or FairScale
- Experience with CUDA-level optimization
- Experience building ML models targeting Apple Silicon
- Experience building large-scale deep learning infrastructure or platforms for distributed model training
- Publication record at Machine Learning conferences such as MLSys, NeurIPS, etc.
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.
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 $171,600 and $302,200, 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.
How to Get Visa Sponsorship as an Efficiency Engineer
Lead with measurable process improvements
Efficiency Engineers are hired to move numbers. Quantify every project on your resume: cycle time reduced, throughput increased, waste eliminated. Hiring managers in this field respond to data over description, and concrete results signal you can contribute from day one.
Confirm your role qualifies for STEM OPT extension
Efficiency Engineer roles typically fall under industrial or systems engineering SOC codes, which qualify for the 24-month STEM OPT extension. Verify your degree field and employer EVerify enrollment before accepting an offer to protect your full authorization window.
Target operations-heavy industries first
Manufacturing, supply chain, healthcare operations, and logistics firms hire Efficiency Engineers at higher volumes than other sectors. These industries also have established OPT and H-1B sponsorship pipelines, making them more receptive to candidates with time-limited work authorization.
Highlight Lean and Six Sigma credentials
A Green Belt or Yellow Belt certification signals structured problem-solving methodology to employers. For OPT candidates, certifications offset concerns about authorization timelines by demonstrating job-ready skills that reduce training investment and accelerate your contribution to the team.
Address OPT timing transparently in applications
State your OPT start date and STEM extension eligibility clearly in your cover letter or application. Employers unfamiliar with OPT often assume the process is complicated. A one-sentence summary of your authorization timeline removes ambiguity and keeps your application moving forward.
Use internship experience to demonstrate sponsor relationships
If you completed a CPT internship in an operations or engineering role, that employer already understands OPT authorization. Returning to a former internship employer or referencing that relationship in applications signals reduced onboarding risk and familiarity with your technical skills.
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Get Access To All JobsFrequently Asked Questions
Does an Efficiency Engineer role qualify for the STEM OPT extension?
Most Efficiency Engineer positions qualify for the 24-month STEM OPT extension because they align with industrial engineering, operations research, or systems engineering SOC codes covered under the STEM designated degree list. Your employer must be enrolled in E-Verify, and you must file Form I-983 within 10 days of starting. Confirm the SOC code your employer plans to use before your OPT start date.
What types of employers hire Efficiency Engineers on OPT?
Manufacturing firms, third-party logistics providers, consulting companies, and healthcare systems are the most active hirers of Efficiency Engineers. Many of these employers operate at scale and have existing immigration infrastructure for OPT and H-1B sponsorship. Migrate Mate lists Efficiency Engineer openings filtered by OPT sponsorship willingness, so you can focus applications on employers already familiar with the authorization process.
How much time does an OPT student have to find an Efficiency Engineer job after graduation?
You have a 60-day grace period after your program end date to find employment or transfer to a new status. Your OPT authorization period does not begin until the start date listed on your EAD card, so the employment clock starts then, not at graduation. Applying before your program ends is strongly advisable since the 60-day window passes quickly.
Can an Efficiency Engineer role lead to H-1B sponsorship?
Yes. Efficiency Engineer positions typically qualify as H-1B specialty occupations because they require at minimum a bachelor's degree in a specific engineering discipline. Employers in manufacturing and operations consulting have consistent H-1B filing histories. With STEM OPT providing up to 36 months of work authorization total, you have enough time to go through two H-1B lottery cycles while employed.
What should I do if my OPT EAD card hasn't arrived before my start date?
You cannot begin work without a valid EAD card in hand, regardless of your offer letter. If your card is delayed, contact USCIS to confirm the application is processing and request expedited handling if you have documentation of financial hardship or employer impact. Notify your employer immediately so they can adjust your start date without retracting the offer.
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