E-3 Visa Machine Learning Research Jobs
Machine Learning Research roles qualify as E-3 specialty occupations, making Australian professionals eligible for U.S. employer sponsorship without entering a lottery. The E-3 visa is renewable indefinitely in two-year increments, so you can build a long-term research career at U.S. labs, universities, and tech companies without the H-1B visa cap pressure.
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Get Access To All JobsAt Apple, new ideas have a way of quickly becoming extraordinary products, services and customer experiences. Sound is an essential and compelling facet of the customer experience. Apple has assembled a world-class Acoustics team that enables our customers to experience music with delight, communicate with clarity and appreciate our products without disturbance from noise. In Apple Acoustics we work with obsessive attention to detail, directly contributing to products that ship to millions of people around the world.
The Audio System Tuning team is looking for an Acoustics ML and DSP Engineer to innovate on and improve the voice processing features and algorithms in Apple devices. This is an applied, product-focused role. You will develop, tune and ship ML and DSP algorithms for the voice audio front end across iOS, macOS and wireless products. Your work will keep phone and video calls clear and natural for everyone on the call, and make Siri and voice recognition reliable in real-world conditions. In this fast-paced, hands-on role, you will take algorithms from prototype through on-device testing into production, where they reach millions of customers. We’re looking for someone who enjoys turning new ideas into real product improvements, and who thrives while balancing several projects at once.
Description
As an Acoustics ML and DSP Engineer, you will develop new speech enhancement algorithms that combine machine learning and DSP, and take them from prototype to production on Apple devices. You will use and extend existing large-scale data preprocessing, simulation and cloud training pipelines, building new ones where needed. You will tune, optimize and listen to algorithms, and debug issues by tracing them to the data, the model or the signal chain. Your work will improve voice quality and intelligibility for telephony and voice calls in challenging conditions such as echo, double talk and noisy environments, and you will measure the effect of front-end processing on telephony quality and machine listening applications. You will also follow the state of the art in speech processing and adjacent fields, and work cross-functionally with tuning, DSP and audio ML colleagues within the team and with partners across the hardware and software organizations.
Minimum Qualifications
MS with 3+ years of relevant experience, or PhD, in Acoustics, Audio, Electrical Engineering, Computer Science or a related field.
Solid grasp of acoustics and signal processing fundamentals.
Experience shipping audio or speech enhancement ML algorithms from prototype to production.
Proficiency with PyTorch and Python, including version control, testing and reproducible experiments.
Working knowledge of Max/MSP for real-time audio prototyping.
Experience with causal, streaming models under real-time latency and compute constraints.
Experience using, and where needed building, large-scale data and cloud training pipelines, including preprocessing and data simulation.
Working knowledge of speech quality evaluation: objective metrics, telephony quality and echo performance measures, and subjective listening tests.
Understanding of the state of the art in speech processing and adjacent fields.
Enthusiasm for exploring and testing new ideas, with the ability to prioritize and deliver across several projects in parallel in a fast-paced environment.
Team player with strong written and verbal communication, and the ability to work in cross-functional teams.
Preferred Qualifications
Experience with audio DSP, such as echo and double-talk handling, microphone array processing, beam-forming, dynamics processing, EQ and noise suppression.
Experience with hybrid systems that combine classical signal processing and machine learning.
Familiarity with telephony voice quality requirements.
Knowledge of front-end processing for speech recognition and machine listening.
Experience with multi-modal machine learning.
Strong coding and debugging skills (Python and C/C++), plus MATLAB for analysis.
Knowledge of transducers and their acoustic integration.
Curious and eager to try new ideas quickly, while keeping multiple product programs on track.
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 $134,700 and $249,500, 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.
At Apple, new ideas have a way of quickly becoming extraordinary products, services and customer experiences. Sound is an essential and compelling facet of the customer experience. Apple has assembled a world-class Acoustics team that enables our customers to experience music with delight, communicate with clarity and appreciate our products without disturbance from noise. In Apple Acoustics we work with obsessive attention to detail, directly contributing to products that ship to millions of people around the world.
The Audio System Tuning team is looking for an Acoustics ML and DSP Engineer to innovate on and improve the voice processing features and algorithms in Apple devices. This is an applied, product-focused role. You will develop, tune and ship ML and DSP algorithms for the voice audio front end across iOS, macOS and wireless products. Your work will keep phone and video calls clear and natural for everyone on the call, and make Siri and voice recognition reliable in real-world conditions. In this fast-paced, hands-on role, you will take algorithms from prototype through on-device testing into production, where they reach millions of customers. We’re looking for someone who enjoys turning new ideas into real product improvements, and who thrives while balancing several projects at once.
Description
As an Acoustics ML and DSP Engineer, you will develop new speech enhancement algorithms that combine machine learning and DSP, and take them from prototype to production on Apple devices. You will use and extend existing large-scale data preprocessing, simulation and cloud training pipelines, building new ones where needed. You will tune, optimize and listen to algorithms, and debug issues by tracing them to the data, the model or the signal chain. Your work will improve voice quality and intelligibility for telephony and voice calls in challenging conditions such as echo, double talk and noisy environments, and you will measure the effect of front-end processing on telephony quality and machine listening applications. You will also follow the state of the art in speech processing and adjacent fields, and work cross-functionally with tuning, DSP and audio ML colleagues within the team and with partners across the hardware and software organizations.
Minimum Qualifications
MS with 3+ years of relevant experience, or PhD, in Acoustics, Audio, Electrical Engineering, Computer Science or a related field.
Solid grasp of acoustics and signal processing fundamentals.
Experience shipping audio or speech enhancement ML algorithms from prototype to production.
Proficiency with PyTorch and Python, including version control, testing and reproducible experiments.
Working knowledge of Max/MSP for real-time audio prototyping.
Experience with causal, streaming models under real-time latency and compute constraints.
Experience using, and where needed building, large-scale data and cloud training pipelines, including preprocessing and data simulation.
Working knowledge of speech quality evaluation: objective metrics, telephony quality and echo performance measures, and subjective listening tests.
Understanding of the state of the art in speech processing and adjacent fields.
Enthusiasm for exploring and testing new ideas, with the ability to prioritize and deliver across several projects in parallel in a fast-paced environment.
Team player with strong written and verbal communication, and the ability to work in cross-functional teams.
Preferred Qualifications
Experience with audio DSP, such as echo and double-talk handling, microphone array processing, beam-forming, dynamics processing, EQ and noise suppression.
Experience with hybrid systems that combine classical signal processing and machine learning.
Familiarity with telephony voice quality requirements.
Knowledge of front-end processing for speech recognition and machine listening.
Experience with multi-modal machine learning.
Strong coding and debugging skills (Python and C/C++), plus MATLAB for analysis.
Knowledge of transducers and their acoustic integration.
Curious and eager to try new ideas quickly, while keeping multiple product programs on track.
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 $134,700 and $249,500, 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.
See all 795+ E-3 Visa Machine Learning Research Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new E-3 Visa Machine Learning Research Jobs.
Get Access To All JobsTips for Finding E-3 Visa Sponsorship in Machine Learning Research
Frame your research credentials for U.S. employers
Australian PhD and honours degrees translate directly to U.S. specialty occupation standards, but your CV needs to show publication records, conference presentations, and model deployment experience in terms U.S. hiring committees recognise.
Target employers with active DOL LCA filings
Search the DOL's Office of Foreign Labor Certification disclosure data for companies that have filed LCAs for ML research titles. This confirms an employer already understands the E-3 visa process and has sponsored similar roles before.
Clarify the specialty occupation case before accepting an offer
Not every ML title passes the specialty occupation test. Roles framed as general data analysis or software engineering may not qualify. Confirm the job description explicitly requires a degree in computer science, statistics, or a directly related field before you sign.
Use Migrate Mate's E-3 filing service for LCA and consulate prep
Once you have an offer, use Migrate Mate's E-3 filing service to handle your LCA and visa paperwork end-to-end. The LCA must be DOL-certified before your consulate appointment, and timing errors here are the most common cause of delays.
Find ML Research jobs on Migrate Mate
Migrate Mate filters job listings by E-3 sponsorship availability, so you're only seeing employers already set up to hire Australians. Search by ML Research job title to surface active roles without wading through listings that will reject your visa status.
Negotiate your start date around E-3 consulate wait times
Sydney, Melbourne, and Perth consulates have different appointment availability. Build at least four to six weeks between your signed offer and your proposed start date so your employer's LCA certification and your consulate slot align without forcing a rushed rescheduling.
E-3 Visa Machine Learning Research: Frequently Asked Questions
How do I find Machine Learning Research jobs that offer E-3 visa sponsorship?
Migrate Mate is built specifically for this search. It surfaces Machine Learning Research roles from employers already willing to sponsor Australian nationals on an E-3 visa, so you're not filtering out irrelevant listings manually. Because the E-3 has no lottery and relatively low employer cost compared to H-1B, more research-focused employers are open to it than you might expect.
How much does it cost to get an E-3 visa?
Migrate Mate's E-3 filing service covers the entire process for $499, including the Labor Condition Application, visa document preparation, and consulate appointment guidance. Traditional immigration lawyers charge $2,000–$5,000+ for the same work. The E-3 has less paperwork than most work visas, so paying thousands for legal help is usually unnecessary.
Does a Machine Learning Research role qualify as a specialty occupation for E-3 purposes?
Most ML Research positions do qualify, provided the job description requires a bachelor's degree or higher in a specific field such as computer science, machine learning, statistics, or applied mathematics. Roles that only list a degree as preferred rather than required, or that accept any field of study, can fail the specialty occupation test. Review the job description carefully before applying.
How does the E-3 visa compare to H-1B for Machine Learning Research roles?
The E-3 has a 10,500 annual cap that has never been reached, so there's no lottery and no random selection risk. H-1B requires entering an annual lottery where selection is not guaranteed. For ML Research roles, both visas require the employer to file an LCA with DOL and demonstrate prevailing wage compliance, but the E-3 timeline is significantly more predictable.
Can I switch ML Research employers while on an E-3 visa?
Yes, but each new employer must file a fresh LCA with the DOL and you'll need a new E-3 visa stamp before re-entering the U.S. if you travel internationally. If you remain inside the U.S. and your current E-3 status is still valid, you can begin work for a new employer while their LCA is pending, though specific timing rules apply.