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Apple

Applied Machine Learning Research Engineer - Perception Algorithms

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Sunnyvale, California, United States

1d ago
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Job Description

Description

Description
We are looking for a skilled deep learning and computer vision engineer for our team. In this role, you will perform research and development work to design algorithms for challenging real world problems in the domain of scene understanding. Your key responsibilities in this role are: - Research, design, train, and evaluate machine learning/deep learning algorithms to address product goals. - Benchmark and analyze machine learning/deep learning algorithms to understand limitations. - Optimize algorithms for real time and low power constraints. - Support algorithm integration into Apple products. - Collaborate with teams across Apple with multidisciplinary skills.

Minimum Qualifications

Minimum Qualifications
  • MS in Computer Science or related field with focus on machine learning, computer vision, robotics or similar.
  • Experience in designing and training efficient network architectures for a diverse set of tasks e.g. image2image translation tasks (like Semantic Segmentation, Panoptic Segmentation), language-guided visual grounding, etc.
  • Experience with data curation for training vision language models, assessment of vision language model capabilities, introduction of new capabilities into backbones trained with vision-language supervision / self-supervised learning.
  • Consistent track record of researching, inventing and/or shipping advanced machine learning algorithms.
  • Solid mathematical foundation of machine learning and deep learning techniques.
  • Strong coding skills in python (with pytorch) and C/C++.

Key Qualifications

Key Qualifications

Preferred Qualifications

Preferred Qualifications
  • Creativity and curiosity for solving highly complex problems.
  • Experience with designing and training with pipelines which consume large (billion scale) data for training efficient vision language models for edge-devices. This includes writing efficient data loading pipelines, utilizing distributed GPU training framework.
  • Experience with advanced task-specific quality optimization techniques (few-shot learning, meta-learning, domain adaptation, knowledge-distillation) for improving network performance and handling specific failure cases (long-tailed distributions/under-represented classes) for downstream tasks.
  • Strong coding skills in ObjectiveC.
  • Excellent communication and collaboration skills.

Education & Experience

Education & Experience

Additional Requirements

Additional Requirements

Pay & Benefits

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 $143,100 and $264,200, 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.

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  • Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure 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.

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