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AIML- Intern in Machine Learning Research, MLR en Barcelona, Barcelona, Spain

Play a part in the next revolution of machine learning research. Explore new methods, challenge existing metrics or protocol, develop new insightful theories that will change the way we understand machine learning. The Machine Learning Research (MLR) team is looking for a passionate PhD student to investigate the next generation of Machine Learning techniques with particular attention to robustness of foundation models under distribution shift, explainability, and alignment to human decision making. As a member of the MLR team, you will work on some of the most challenging scientific questions, collaborate with world-class machine learning researchers, push forward innovative research agendas and publish ground-breaking research in international conferences.

Descripción del empleo

Key Qualifications
  • Proven expertise in machine learning with a passion for robust representation learning, interpretability, and/or causal approaches to machine learning (experience with foundation models is a plus).
  • Strong publication record in relevant conferences (e.g. NeurIPS, ICML, ICLR, AISTATS, AAAI, ACL, FAccT).
  • Good programming skills in Python.
  • Hands-on experience working with deep learning toolkits such as PyTorch and Jax.
  • Strong mathematical skills in linear algebra and statistics.
  • Ability to formulate a research problem, design, experiment and implement solutions.
  • Ability to work collaboratively.
Description
Are you passionate about advancing the state-of-the-art in ML and pursuing great innovation? You will help to identify gaps in the research field, define the internship research agenda, and develop innovative ML methods for challenging problems that will affect the scientific research community, future Apple products, and society. You will receive technical mentorship and guidance, while providing your enthusiasm and skills in order to research innovative solutions and publish your results in international conferences. You have the ability to work both independently and collaboratively together with other researchers and product teams. You will have the chance to work in a dynamic team that is able to tackle innovative Machine Learning problems at scale. You will be responsible for delivering ML research aligned with the core values of Apple, ensuring the highest standards of quality, scientific rigor, innovation, and respect for user privacy. Apple’s most important resource, our soul, is our people. Apple benefits help further the well-being of our employees and their families in meaningful ways. No matter where you work at Apple, you can take advantage of our health and wellness resources and time-away programs. We’re proud to provide stock grants to employees at all levels of the company, and we also give employees the option to buy Apple stock at a discount — both offer everyone at Apple the chance to share in the company’s success. You’ll discover many more benefits of working at Apple, such as programs that match your charitable contributions, reimburse you for continuing your education and give you special employee pricing on Apple products. Apple benefits programs vary by country and are subject to eligibility requirements. 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. Apple is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Apple is a drug-free workplace.
Education & Experience
Pursuing a PhD in Machine Learning, Computer Science, Statistics, or a related technical field.
Additional Requirements

Información extra

Status
Inactiva
Localización
Barcelona, Barcelona, Spain
Tipo de contrato
Tiempo completo
Tipo de trabajo
Cajero
Carnet de conducir
No
Vehículo
No
Carta de motivación
No

Trabajo de cajero | Tiempo completo