Multimodal Generative Modeling Research Engineer - SIML, ISE
Location
Cupertino, CA | United States
Job description
Are you excited about Generative AI? Are you interested in working on cutting edge generative modeling technologies to enrich billions of people? We have multiple ongoing efforts involving generative models. We are looking for technical leaders experienced in training, adapting and deploying large scale ML models with a focus on multimodal understanding and generation.
We are the Intelligence System Experience (ISE) team within Apple’s software organization. The team works at the intersection between multimodal machine learning and system experiences. System Experience (Springboard, Settings), Keyboards, Pencil & Paper, Shortcuts, User Safety are some of the experiences that the team oversees. These experiences that our users enjoy are backed by production scale ML workflows. Visual Understanding of People, Text, Handwriting & Scenes, multilingual NLP for writing workflows, knowledge extraction, conversation understanding and text generation, behavioral modeling for proactive suggestions, and privacy preserving learning are areas our multi disciplinary ML teams focus on.
We are looking for senior research engineers to architecture and innovate multimodal ML technologies and ensure these technologies can be safety deployed to the real world. An ideal candidate has the ability to lead diverse cross functional efforts ranging from ML modeling, prototyping, validation and private learning. An ideal candidate will have proven ML & Generative AI fundamentals and ability to turn research contributions into products. Industry experience in Vision-Language multimodal modeling, Reinforcement and Human Preference Learning, multimodal safety and alignment would be important needs.
SELECTED REFERENCES TO OUR TEAM’S WORK:
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Key Qualifications
- Expertise within ML and Generative Modeling fundamentals
- Experience adapting pre-trained Vision/Language models for downstream tasks & human alignment
- Modeling experience at the intersection of NLP and vision
- Familiarity with distributed training
- Proficiency in using ML toolkits, e.g., PyTorch
- You're aware of the challenges associated to the transition of a prototype into a final product
- Proven record of research innovation and demonstrated leadership in both applied research and development
Description
We are looking for a candidate with a proven track record in applied ML research. Responsibilities in the role will include training large scale multimodal (2D/3D vision-language) models on distributed backends, deployment of compact neural architectures efficiently on device, address growing set of safety challenges to make the model robust and aligned with human values. Ensuring quality in the wild, with an emphasis on model safety, fairness and robustness would constitute a meaningful part of the role. You will be interacting very closely with a variety of ML researchers, software engineers, hardware and design teams cross functionally. The primary responsibilities of the role would center on enriching multimodal capabilities of large language models. The user experience initiative would focus on aligning image/video content to the space of LMs for visual actions & multi-turn interactions.
Education & Experience
M.S. or PhD in Electrical Engineering, Computer Science or a related field (mathematics, physics or computer engineering), with a focus on computer vision and/or machine learning; or comparable professional experience.
Additional Requirements
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 $170,700.00 and $300,200.00, 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 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.
We are looking for a candidate with a proven track record in applied ML research. Responsibilities in the role will include training large scale multimodal (2D/3D vision-language) models on distributed backends, deployment of compact neural architectures efficiently on device, address growing set of safety challenges to make the model robust and aligned with human values. Ensuring quality in the wild, with an emphasis on model safety, fairness and robustness would constitute a meaningful part of the role. You will be interacting very closely with a variety of ML researchers, software engineers, hardware and design teams cross functionally. The primary responsibilities of the role would center on enriching multimodal capabilities of large language models. The user experience initiative would focus on aligning image/video content to the space of LMs for visual actions & multi-turn interactions. M.S. or PhD in Electrical Engineering, Computer Science or a related field (mathematics, physics or computer engineering), with a focus on computer vision and/or machine learning; or comparable professional experience.
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