Sobre este puesto de Lead Machine Learning Scientist, New AI Products and Platforms en The New York Times
The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It’s why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It’s why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it’s why our business strategy centers on making journalism so good that it’s worth paying for.
About the Role, Mission or Department Overview
The New York Times is hiring a Lead 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 provide technical leadership to a team of ML scientists developing embedding models and semantic retrieval algorithms to power new A.I. experiences across our products. Your work will allow teams across the company to build, deploy, and manage applications that use large language models to promote our journalism and our business. Your team will design and train embedding models for representation learning and fine-tune language models for custom use cases and content enrichment. You will report to our Director, Machine Learning. This is a hybrid remote/in-office role.
Responsibilities:
- You will lead the design and training of embedding models for representation learning, for example using transformer encoders and Two Tower architectures.
- You will lead the fine-tuning, adaptation, and evaluation of language models for custom product use cases and content enrichment, including information extraction from Times content at scale
- You will productionalize embedding models and language models while working closely with engineering teams, to integrate ML and AI into user-facing products throughout The Times
- You will help to define shared practices around evaluation, responsible A.I. use, and what "good" is inside an organization where judgment and independence are important
- You will identify novel project opportunities to solve critical problems and act on those proposals
- You will scope ongoing product improvements, prioritizing requests from your team
- You will build and facilitate relationships across the organization to ensure you meet our projects' goals.
- 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 plus 4+ years experience, or 7+ years experience, in machine learning, statistics, computer science, computational social science, or another quantitative/computational discipline
- 4+ years of experience in creatively reframing our challenges as Machine Learning tasks
- 4+ years of experience with data cleaning, preparation, feature engineering, and model selection techniques
- 2+ years of experience coding and deploying in production environments using Python, developing and deploying complex algorithms that are integrated into company process
- 2+ years of experience building production systems that use LLMs, vision-language models, graph neural networks, or other deep learning models to solve user-facing problems
- 1+ years of experience mentoring peers or junior ML scientists through pairing and algorithm, model, and code review
Preferred Qualifications:
- PhD or Master's research experience in Applied AI
- 1+ years of experience with information retrieval or search systems
- 2+ years of experience collaborating cross-functionally with product managers and software engineers
- 2+ years of experience scoping and staging work into well-defined milestones and delivering on communicated timelines
REQ-020336
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.
The New York Times Company is committed to being the world’s best source of independent, reliable and quality journalism. To do so, we embrace a diverse workforce that has a broad range of backgrounds and experiences across our ranks, at all levels of the organization. We encourage people from all backgrounds to apply.
We are an Equal Opportunity Employer and do not discriminate on the basis of an individual's sex, age, race, color, creed, national origin, alienage, religion, marital status, pregnancy, sexual orientation or affectional preference, gender identity and expression, disability, genetic trait or predisposition, carrier status, citizenship, veteran or military status and other personal characteristics protected by law. All applications will receive consideration for employment without regard to legally protected characteristics. The U.S. Equal Employment Opportunity Commission (EEOC)’s Know Your Rights Poster is available here.
The New York Times Company will provide reasonable accommodations as required by applicable federal, state, and/or local laws. Individuals seeking an accommodation for the application or interview process should email reasonable.accommodations@nytimes.com. Emails sent for unrelated issues, such as following up on an application, will not receive a response.
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