Machine Learning Fellow - Human Frontier Collective (US)
申请人必须获得在美国工作的授权,签证赞助商不允许参与该职位。关于计划的人际边境集体 (HFC) 奖学金汇聚顶尖研究人员和领域专家合作,共同制定 AI 未来的影响力高的工作。作为 HFC Fellow,你将用学术和专业知识来帮助设计,评估和解释先进的生成 AI 系统,同时接触到尖端研究和与领先思想家跨学科网络合作。你将做什么 · ML 项目:与我们的合作伙伴 AI 实验室和平台一起参与高影响性项目的邀请。通过设计,审查和优化 PyTorch 模型,评估复杂的 ML 代码和人工智能生成实现效率和正确度以及咨询 GPU 优化,扩展和交易方面,帮助模型了解现实世界深层学习工作流程。· HFC 社区:工作以外,你将成为支持性的跨学科创新者和思想领导人网络的一部分。他们致力于推动跨领域的边界人工智能发展。· 贡献研究出版物:与 Scale 的研究团队合作编写技术报告和研究论文增强你的学术可见性和专业认可 (例如预测,propensityBench,专业推理基准).谁应申请?· 教育:计算机科学博士或计算机工程或相关领域的博士学位。· 专业背景:1-3年以上机器学习工程师或数据科学家经验:·技能:强大的 Python 和现代 ML 框架 (PyTorch, TensorFlow) 的熟练知识。与云基础设施 (AWS) 和 MLOps 工具 (Docker, Langchain) 有经验是优势的。·专业思维:以细节为导向,具有应用人工智能研究和协作热情的创新思想家。为什么加入 HFC? ·专业发展:高影响力专家通过审查项目,咨询角色和研究扩大他们的影响力,同时加深他们的 AI 专业知识,加强分析和解决问题的技能,并参与科学和技术领域先进的 AI 应用程序。·加入顶级网络:与全球工程师和专家网络合作广告。
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PLEASE NOTE: This is a fully remote, 1099 independent contractor opportunity with an estimated duration of six months and the potential for extension. To be eligible, candidates must be authorized to work in the United States; visa sponsorship is not available for this role.
About the Program
The Human Frontier Collective (HFC) Fellowship brings together top researchers and domain experts to collaborate on high-impact work that are shaping the future of AI. As an HFC Fellow, you’ll apply your academic and professional expertise to help design, evaluate, and interpret advanced generative AI systems—while gaining exposure to cutting-edge research and working alongside an interdisciplinary network of leading thinkers.
What You'll Do
- ML Projects: Get invited to engage in high-impact projects with our partnered AI labs and platforms. Help models understand real-world deep learning workflows by designing, reviewing, and optimizing PyTorch models, evaluating complex ML code and AI-generated implementations for efficiency and correctness, and advising on GPU optimization, scaling, and trade-offs.
- HFC Community: Beyond the work, you’ll become part of a supportive, interdisciplinary network of innovators and thought leaders committed to advancing frontier AI across domains.
- Contribute to Research Publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition (e.g., SciPredict, PropensityBench, Professional Reasoning Benchmark).
Who Should Apply
- Education: PhD or postdoctoral degree in Computer Science, Computer Engineering, or a related field.
- Professional Background: 1-3+ years of experience as a Machine Learning Engineer or Data Scientist.
- Skills: Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow). Experience with cloud infrastructure (AWS) and MLOps tools (Docker, Langchain) is a plus.
- Professional Mindset: Detail-oriented, innovative thinker with a passion in applied AI research and a commitment to collaboration.
Why Join the HFC?
- Professional Development: High-impact experts expand their influence through review projects, advisory roles, and research, while deepening their AI expertise, strengthening analytical and problem-solving skills, and engaging with pioneering AI applications in science and technology.
- Join a Top-Tier Network: Collaborate with a global network of engineers and experts to advance responsible AI through impactful, flexible research and training. 80% of our members come from leading institutions.
- Flexible Schedule: Set your own schedule, with flexible 10–40 hour weeks that fit around your life and other commitments.
- Competitive Pay: Project pay rates vary across platforms and are depending on a number of factors, including but not limited to; projects, scope, skillset, and location.
Application Process
- Apply: We review applications on a rolling basis.
- Interview: Candidates will get to discuss their research experience, professional background, and alignment with our mission to advance human-centered AI.
- Join the Collective: Successful candidates will receive an invitation to join the Human Frontier Collective Fellowship.
PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
About Us:
At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst& Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.
We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.
We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at . Please see the United States Department of Labor's Know Your Rights poster for additional information.
We comply with the United States Department of Labor's Pay Transparency provision.
PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Originally posted on Himalayas