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Machine Learning Engineer and Researcher
2 months ago
We are seeking a highly skilled Machine Learning Engineer and Researcher to join our Data and Machine Learning Innovation (DMLI) team at Apple. As a member of this team, you will have the opportunity to work on ambitious, curiosity-driven long-term research projects that will impact the future of Apple and our products.
Key Responsibilities- Apply innovative research in machine learning to tackle complex data annotation and product evaluation problems.
- Develop solutions that significantly impact future Apple products and the broader ML development ecosystem.
- Work with a multidisciplinary team to build machine-based grading models that reduce annotation costs and turnaround time, and to build pipelines that automate the assessment of quality of data used for training foundational models and adapter models.
- Showcase your groundbreaking research work by publishing and presenting at premier academic venues.
As a Machine Learning Engineer, you will be entrusted with the critical role of applying innovative research in ML to tackle complex data annotation and product evaluation problems. Your work may span a variety of topics, including:
- Using internal and external LLMs to build grading models and integrate the grading models into the evaluation pipelines to reduce turnaround time and automate evaluation of quality of curated data.
- Conducting research to improve efficacy of data curation through identifying grading errors, bias, distribution disparity between training and applications, thus, improve scaling of model performances with respect to data size and model size.
- Uncovering patterns in data and using modern statistical and ML-based methods to model data distributions. This will aid in discovering anomaly for mitigation and understanding model performance caveats caused by out-of-distribution samples and edge cases.
- Employing data selection techniques such as novelty detection, active learning, and core-set selection for diverse data types like images, 3D models, natural language, and audio.
- Excellent collaboration and communication skills with a focus on the user experience.
- 5+ years of experience with developing and evaluating ML applications, and demonstrated experience in understanding and improving data quality.
- Experience writing automated unit, integration, and acceptance tests, and using continuous integration systems.
- Experience with database and SQL skills.
- B.S. in Machine Learning, Computer Science, Statistics, Operations Research or related areas.
- Proven expertise in machine learning with a passion for model evaluation and applications.
- Experience with natural language processing (NLP), and large language models, such as BERT, GPT, or Transformers.
- Staying on top of emerging trends in LLMs.
- Strong programming skills and hands-on experience using the following languages or deep learning frameworks: Python, PyTorch, or Jax.
- Demonstrated publication record in relevant conferences (e.g. ACL, EMNLP, NeurIPS, ICML, ICLR, etc) is a plus.
- Ph.D. in Machine Learning, Computer Science, Statistics, operations Research or related areas.
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 $135,400 and $250,600, 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.
