Interested in this AI/ML Engineer role at The New York Times?
Apply Now →About This Role
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.
Mission Overview \& Responsibilities:
We are looking for a Research Lead with a passion for ensuring that reader\-centric insights are at the heart of the product development process. You will lead a variety of end\-to\-end research projects that drive strategy for the New A.I. Products and Platforms (NAPP) Mission. You will work with a cross\-functional digital product team, including Product, Design, Editorial, Engineering and Marketing. You will report to the Managing Director of News Products and Audience Insights at The New York Times.
The mission of the New York Times Audience Insights team is to help The Times grow by understanding our audience. The Audience Insights team is centralized team of researchers working with teams across The New York Times. We utilize product, human\-centered design, innovation, market and UX research, and we draw from principles in the social sciences (Psychology, Anthropology, Sociology and Behavioral Economics).
This is a hybrid role based in our New York City office.
Responsibilities:
- Lead a human\-centered design approach for Products teams, inspiring colleagues to build innovative product features grounded in user needs to drive NAPP and company goals.
- Use research\-based insights and GenAI tools for rapid prototype iteration.
- Own evaluation for quality and editorial integrity: Create frameworks to assess the success of A.I. prototypes and products.
- Build innovative solutions using AI tools to support certain parts of the research process.
- Champion A.I. innovation and ethics: Stay up to date with industry trends, new research methodologies, LLM advancements, and emerging technologies. Champion the ethical and responsible use of AI, ensuring our tools uphold our standards of accuracy and objectivity.
- Complement research with behavioral data, proprietary and industry research, and A/B testing results to provide a holistic view of our users.
- Work with Audience Insights researchers across News Product, Marketing, Cooking, Wirecutter, The Athletic and Games to identify opportunities to collaborate and avoid duplicative product work.
- Manage external research vendors to support moderation, fieldwork, and analysis, ensuring high\-quality and efficient project execution.
- Contribute to the collaborative culture of Audience Insights and the NAPP Mission; help The New York Times understand, and build empathy for, our audiences.
- 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:
- 8\+ years of research and insights experience.
- Experience researching chat interfaces or GenAI search tools and using a range of GenAI tools and features in your work.
- Experience moderating qualitative research and facilitating brainstorms and workshops with cross\-functional partners.
- Mastery of a range of research methods . These methods include participatory design, in\-person and remote interviews, ethnographies, co\-creation, and user\-initiated feedback tools. Additionally, surveys, card\-sorting, and usability studies are also part of the range.
- Experience executing qualitative and quantitative research and selecting the right approach based on the problem to be solved.
- Experience synthesizing complex findings into compelling narratives and visualize insights for diverse audiences.
Preferred Qualifications:
- Experience conducting research for early\-stage 0\-1 product development, helping teams identify opportunities, validate concepts, and shape new product experiences.
- Experience working in rapid prototyping environments, using research to inform iterative product development and experimentation.
- Experience building alignment among cross\-functional stakeholders, including Product, Design, Engineering, Editorial, and Marketing partners.
- Experience presenting to stakeholders, senior management, and fellow researchers.
- A deep curiosity about the role of AI in shaping the future of information, media, and journalism.
REQ\-020138
\#LI\-Hybrid
The annual base pay range for this role is between:
$140,000 \- $155,000 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.
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.
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 [email protected]. Emails sent for unrelated issues, such as following up on an application, will not receive a response.
The Company encourages those with criminal histories to apply, and will consider their applications in a manner consistent with applicable "Fair Chance" laws, including but not limited to the NYC Fair Chance Act, the Los Angeles Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
Please beware of fraudulent job postings. Scammers may post fraudulent job opportunities, and they may even make fraudulent employment offers. This is done by bad actors to collect personal information and money from victims. All legitimate job opportunities from The New York Times will be accessible through The New York Times careers site. The New York Times will not ask job applicants for financial information or for payment, and will not refer you to a third party to do so. You should never send money to anyone who suggests they can provide employment with The New York Times.
If you see a fake or fraudulent job posting, or if you suspect you have received a fraudulent offer, you can report it to The New York Times at [email protected]. You can also file a report with the Federal Trade Commission or your state attorney general.
Salary Context
This $140K-$155K range is below the median for AI/ML Engineer roles in our dataset (median: $180K across 1937 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At The New York Times, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills in Demand for This Role
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $181,170 based on 12,692 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($147K) sits 19% below the category median. Disclosed range: $140K to $155K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
The New York Times AI Hiring
The New York Times has 3 open AI roles right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $131K - $160K.
Location Context
AI roles in New York pay a median of $211,000 across 2,643 tracked positions. That's 5% above the national median.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (112) are outnumbered by mid-level (1,798) and senior (1,516) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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