The New York Times is hiring a Machine Learning Scientist to join the New A.I. Products & Platforms mission. We are a team building the next generation of reader-facing A.I. experiences for one of the world's most trusted news organizations. You will join a team of ML scientists developing embedding models and retrieval algorithms to power new A.I. experiences across our products. You will design and train embedding models for representation learning and fine-tune language models for custom use cases and content enrichment. Your work will allow teams across the company to build, deploy, and manage applications that use large language models (LLMs) to promote our journalism and our business. You will report to our Director, Machine Learning. This is a hybrid remote/in-office role. Responsibilities: - You will design and train embedding models for representation learning, for example using transformer encoders and Two Tower architectures. - You will fine-tune and evaluate language models for custom use cases and content enrichment. - You will contribute to shared practices around evaluation, responsible A.I. use, and what "good" is inside an organization where judgment and independence are important - You will implement and deploy machine learning and AI research with robustness and reproducibility, with consideration of risks and trade-offs - You will adapt or develop ML and AI algorithms in cases when existing techniques are insufficient, while implementing simple approaches - You will communicate complex ideas in machine learning and AI while collaborating with all kinds of colleagues in engineering, analytics, product management, marketing, editorial, and executive leadership groups - Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world. Basic Qualifications: - PhD, MS + 2 years experience, or 3+ years work experience in machine learning, statistics, computational social science, applied mathematics, or another quantitative/computational discipline - 2+ years experience with open source machine learning or statistical analysis tools - 2+ years coding experience in Python - 2+ years experience in SQL and manipulating large structured or unstructured datasets for analysis - 1+ years of experience with deep learning architectures, fine-tuning, embeddings and Pytorch or Tensorflow Preferred Qualifications: - 1+ years of experience with information retrieval or search systems - 1+ years of experience translating ambiguous business questions into machine learning problems - 1+ years of experience building data products, either internal or consumer-facing REQ-020337 The annual base pay range for this role is between: $121,000-$141,000 USD For roles in the U.S., dependent on your role, you may be eligible for variable pay, such as an annual bonus and restricted stock. Benefits may include medical, dental and vision benefits, Flexible Spending Accounts (F.S.A.s), a company-matching 401(k) plan, paid vacation, paid sick days, paid parental leave, tuition reimbursement and professional development programs. For roles outside of the U.S., information on benefits will be provided during the interview process. We're excited to learn more about you and your experience. To keep our hiring process as fair and authentic as possible, we ask that you submit your own work and not use GenAI tools to generate substantive content during the application and interview process. If you're an Engineering candidate, we'll let you know what specific GenAI tools you are permitted to use for your technical assessment.