Expoint – all jobs in one place
מציאת משרת הייטק בחברות הטובות ביותר מעולם לא הייתה קלה יותר
Limitless High-tech career opportunities - Expoint

Apple Senior Applied ML Scientist 
United States, Washington, Seattle 
113242613

08.06.2025
This role involves using generative models and optimization tools and methods to produce diverse and representative data when real-world data is scarce, sensitive, or prohibitively expensive to collect. This researcher collaborates closely with other ML scientists and data scientists to understand data requirements, optimize generation pipelines, and ensure the synthetic data supports model generalization and robustness.In addition to research and technical implementation, the role also requires developing quality control mechanisms, such as human-in-the-loop feedback loops, to ensure that synthetic datasets are valid. This work will support applications in diverse domains.
  • Strong foundation in ML fundamentals.
  • Experience or proven interest in designing and implementing AI-driven approaches to data generation.
  • Experience developing evaluation metrics and systems.
  • Proficiency in software engineering best practices.
  • Proficiency in statistical analysis and data visualization.
  • Strong proficiency in Python.
  • Strong proficiency in PyTorch, TensorFlow, or Jax.
  • Excellent communication skills with a proven ability to engage diverse stakeholders.
  • Experience with MLOps standards, including containerization, orchestration (e.g., Kubernetes), and CI/CD.
  • 5+ years with a Master's degree, 3+ years with a PhD, or equivalent practical experience.
  • Experience building scalable data generation pipelines and human-in-the-loop workflows
  • Experience developing and owning high-impact, developer-facing systems and tools.
  • Experience with LLM orchestration frameworks such as Lanchain and DSPy
  • Experience adapting and aligning LLMs through various training strategies, e.g. continued pre-training, supervised fine-tuning, and reinforcement learning.
  • Expertise in uncertainty estimation and calibration, automated prompt optimization, active learning, or related problem spaces.
  • Experience with large-scale data processing frameworks, e.g. Spark, PySpark, Dask, or Ray.
  • Track record of contributions to open-source ML projects or publications in top-tier ML conferences (e.g., NeurIPS, ICML, ACL).
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.