{"title": "AIML - Sr Machine Learning Engineer, Data and ML Innovation", "summary": "Do you want to play a part in the next revolution in large languages models, contribute to products that are redefining mobile and desktop computing, and work with the people who built the intelligent assistant and search products that helps millions of people get things done \u2014 just by asking or typing? The vision for the AIML Data organization is to improve products by using data as the voice of our customers. As a Sr Machine Learning Engineer on the team, you will build algorithms and data applications that leverage the power of data (real and synthetic) to improve model training efficiency and performance.", "description": "We are looking for people with a track record in building products and relationships to affect decisions. Join us, and impact hundreds of millions of customers across billions of their interactions with intelligent features on iPhone, iPad, HomePod, Mac, to CarPlay, and \uf8ffTV across more than 30 languages. You will partner closely with data engineering and data science partners as well as product teams to identify areas for product and model quality hillclimb. Develop micro-services that enable easier, programmatic integration of model training processes and frameworks across the AIML organization. Use appropriate modeling techniques (large model fine-tuning included) to extract high value training datasets, verified through ablation studies. Apply ML rigor and complex algorithms in high impact projects. Evangelize findings throughout the organization to ensure integration of information into operational processes.", "key_qualifications": "Derive engineered metrics and statistical information out of massive and complex datasets (e.g. Spark MLlib, Druid, Solr, Kafka). Have built robust feature extraction and ML training pipelines and have a keen eye for where to automate (e.g. Airflow). Have done prototype-to-production development of ML models. You care about improving training performance by researching into the latest algorithms. You also value scaling inferences by applying CPU/GPU resources in a parallelized fashion and have a strong foundation in data structures and optimization algorithms. Are knowledgeable in classic machine learning algorithms (SVM, Random Forest, Naive Bayes, KNN etc). Good understanding of bias/variance trade-off, regularization, dimension reduction. Have expertise in modern deep learning techniques via packages such as PyTorch, Keras/Tensorflow. Care about data-generating processes, not just modeling them, but understanding the actual human and computational behavior from which data emerges.", "preferred_qualifications": "", "education_experience": "B.S. or advanced degrees in Computer Science, Electric Engineering, or other related engineering programs.", "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 $166,600 and $296,300, 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\u2019s 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\u2019s Employee Stock Purchase Plan. You\u2019ll 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 \u2014 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.", "company": "apple"}