Role Overview
Thenewyorktimes is hiring a entry-level ML Ops Engineer, Machine Learning & AI. This is a full-time role in New York. posted yesterday. Full responsibilities, required qualifications, and the apply link are listed in the description below.
Resume Keywords to Include
Make sure these keywords appear in your resume to improve ATS scoring
Job description
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:
Machine Learning (ML) at the New York Times enhances the experience of our 150 million digital readers from around the globe and grows our subscriber base through content recommendations and personalizations.
The Machine Learning & AI team builds and maintains the infrastructure that hosts all of The New York Times real-time ML inference models, including both data and compute. Our partners are Data Scientists that build and deploy their ML models on the ML platform. On the other end, our partners are engineering systems that call these hosted models at scale with low-latency and Service Level Agreements guaranteed by our platform.
As an MLOps Engineer you will partner with product, data science and ML platform engineers to build and maintain the infrastructure that powers the machine learning lifecycle. You will automate and refine the training, deployment, monitoring, and management of our ML models.
This role reports to the Senior Engineering Manager of Data Management Infrastructure.
Responsibilities:
-
Build and Automate ML Pipelines: by owning robust CI/CD pipelines for automated model training, validation, deployment, and retraining.
-
Productionalize Models: Build the process for packaging, containerizing, and deploying ML models as scalable, low-latency, and highly-available services.
-
Monitoring and Operations: Implement and manage comprehensive monitoring for production models, tracking system health, data drift, and model performance degradation.
-
Tooling and Infrastructure: Manage and evolve our MLOps toolchain, including model registries, feature stores, experiment tracking systems, and model serving platforms.
-
Collaboration and Support: Partner with data scientists to understand model requirements and optimize them for production. Support software engineers in integrating with ML services.
-
Best Practices and Governance: Champion and enforce MLOps best practices for reproducibility, versioning (data, code, model), testing, and governance.
-
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:
-
2+ years of software engineering or DevOps experience with a focus on MLOps, automation, and infrastructure
-
2+ years of experience programming in Python or Go
-
Experience building and managing CI/CD pipelines (e.g., Github Actions, Jenkins, GitLab CI)
-
Hands-on experience with containerization and orchestration (e.g., Docker, Kubernetes)
-
Cloud platform experience (AWS, GCP) and familiarity with infrastructure-as-code (e.g., Terraform, CloudFormation)
Preferred Qualifications:
-
Experience with MLOps tools (e.g., MLflow, Kubeflow)
-
Experience with the machine learning model lifecycle, from experimentation to production
-
Experience with data processing frameworks (e.g., Spark, Dask, or Ray)
-
Experience with low-latency no-sql datastores (BigTable, Dynamo, etc)
-
Familiarity with monitoring and observability stacks (e.g., Prometheus, Grafana, Datadog, or ELK)
-
Knowledge of data engineering pipelines and orchestration tools (e.g., Airflow, Prefect)
REQ-019522
#LI-hybrid
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.
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.
For information about The New York Times' privacy practices for job applicants click here.
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 NYTapplicants@nytimes.com. You can also file a report with the Federal Trade Commission or your state attorney general.
About Thenewyorktimes
Thenewyorktimes
151 other open roles at Thenewyorktimes on TryApplyNow.
Frequently Asked Questions
How do I apply for the ML Ops Engineer, Machine Learning & AI position at Thenewyorktimes?
Use the Apply button above to submit your application directly to Thenewyorktimes. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.
Where is the ML Ops Engineer, Machine Learning & AI position at Thenewyorktimes located?
This position is based in New York. Thenewyorktimes has not indicated remote or hybrid options for this role, so candidates should plan for on-site work.
What does a ML Ops Engineer, Machine Learning & AI at Thenewyorktimes earn?
Thenewyorktimes has not disclosed a salary range in this posting. Many employers share specifics later in the interview process; you can also ask during a recruiter screen if compensation transparency is important to you.
When was the ML Ops Engineer, Machine Learning & AI role at Thenewyorktimes posted?
This role was posted on July 8, 2026 (yesterday). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.
Is the ML Ops Engineer, Machine Learning & AI role at Thenewyorktimes entry-level?
Yes. This is an entry-level position. Strong candidates typically have 0-2 years of relevant work experience, internships, or significant project work. Read the full description for any specific qualification requirements Thenewyorktimes has listed.
More Jobs at Thenewyorktimes
View all →Video Journalist, Reporter Video
Thenewyorktimes
Video Graphics Editor, Opinion Shows
Thenewyorktimes
Vice President, Cybersecurity and Deputy Chief Information Security Officer
Thenewyorktimes
Vice President, Associate General Counsel and Assistant Secretary
Thenewyorktimes
Vice President, Assistant General Counsel
Thenewyorktimes
AI-powered job search
Get every job scored to your resume
Upload your resume and get jobs ranked, your resume tailored, and employee contacts found automatically.
Get started freeNo credit card to start