REGISTRIEREN

Jobbörse

Finde Jobs in deiner Nähe – ob vor Ort, hybrid oder remote.
  • Ähnliche Jobs zu: AIML - Staff Machine Learning Engineer
XX
AIML - Machine Learning Engineer - Computer Vision & Audio, MINDApple • Seattle, Washington, United States
Jetzt Bewerben
XX

AIML - Machine Learning Engineer - Computer Vision & Audio, MIND

Apple
  • US
    Seattle, Washington, United States
  • US
    Seattle, Washington, United States
Jetzt Bewerben

Über

AIML - Machine Learning Engineer - Computer Vision & Audio, MIND Seattle, Washington, United States Machine Learning and AI
The Machine Intelligence, Neural Design (MIND) team, part of Apple’s AIML organization, is leading Apple-wide innovation on HW/SW co-design for efficient inference. With roots in ML, computer vision, and energy efficiency research, our team is strategically positioned to contribute to diverse initiatives ranging from shipping features in well-known Apple products to ambitious, long-term research projects.
We are seeking a hands‑on Machine Learning Engineer to drive the data & evaluation lifecycle for our production models. In this role, you will focus on designing and scaling high‑performance data processing pipelines, ensuring data quality, performing in-depth failure analysis on production models, and implementing advanced data augmentation techniques to boost model performance. This includes but is not limited to crafting creative techniques to analyze audio & video datasets, designing metrics to understand user behavior & evaluate performance of machine learning models. You will innovate across the entire end‑to‑end ML production pipeline, bridging the gap between hardware, software, and modeling, ensuring our ML systems are robust, efficient, and scalable.
Description We are seeking a Machine Learning Engineer to design and deliver innovative features and models that advance our ML systems. In this role, you will scale model evaluation workflows, build robust data pipelines, and optimize performance across the stack.
Pipeline Scaling & Optimization: Design, build, and maintain scalable ETL/ELT data pipelines using tools like Spark, & Airflow to handle large‑scale datasets. Optimize existing pipelines for efficiency, latency, and cost.
Data Augmentation & Synthesis: Research and implement advanced data augmentation techniques (e.g., GANs, semantic augmentation, synthetic data generation) to address data scarcity and imbalanced datasets.
Data Quality & Monitoring: Implement data observability and automated data validation checks to identify data drift, schema violations, and outliers in real‑time.
Failure Analysis & Debugging: Perform root‑cause analysis on production model failures, diagnosing issues between data inputs and model outputs using advanced statistical methods.
Model Evaluation: Collaborate with other machine learning engineers to productize models, implementing robust evaluation frameworks, including experimentation and performance monitoring.
Minimum Qualifications
Proficiency in working with unstructured data, specifically video & audio signals, for object detection, pattern recognition, feature extraction and segmentation.
Proficiency with Python and deep learning frameworks like PyTorch.
Expertise in designing metrics, and conducting metric change & performance analysis for model evaluation.
Strong problem solving skills in analyzing complex, ambiguous problems and clearly presenting sophisticated technical concepts to both expert and non‑expert audiences.
Proven track record of contributing to cross functional projects in a collaborative environment.
Self‑motivated and curious with creative and critical thinking capabilities and drive to figure out and improve how things work.
High tolerance for ambiguity. You find a way through. You anticipate. You connect and synthesize.
Strong verbal and written communications skills with demonstrated experience in authoring & presenting analytical insights via papers & presentations.
Experience with large scale training ML models including deep learning based models.
Experience with shipping ML features and products.
Master’s degree or equivalent experience in a technical or quantitative field.
Preferred Qualifications
Experience with shipping ML features and products
Experience with GPU‑based distributed training & evaluation.
Background in Computer Vision (image augmentation), Audio and Natural Language Processing.
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 $139,500 and $258,100, 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 .
Apple accepts applications to this posting on an ongoing basis.
#J-18808-Ljbffr
  • Seattle, Washington, United States

Sprachkenntnisse

  • English
Hinweis für Nutzer

Dieses Stellenangebot stammt von einer Partnerplattform von TieTalent. Klick auf „Jetzt Bewerben”, um deine Bewerbung direkt auf deren Website einzureichen.

Jobbörse: 10'000+ Jobs in deiner Nähe – vor Ort, hybrid oder remote