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Lead ML Engineer

Englewood Cliffs, New Jersey, United States

Live, first seen by us 41 days ago
Pay
Pay not listedSimilar roles state $166K–$240K
Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
From the employer’s posting
Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting

What you’ll work on

Full posting
  • Set the ML/AI technical vision and roadmap tied to newsroom and business priorities

  • Architect end-to-end ML systems from data through training, evaluation, deployment and monitoring

  • Define offline and online model evaluation and monitoring frameworks with feedback loops

  • Build reusable AI primitives, APIs and shared services across VERSANT brands

  • Assess AI vendors and guide teams in choosing foundation models and tooling

From the employer’s posting
Set the technical vision for ML/AI at VERSANT, translating business and newsroom priorities into a focused, high-impact execution roadmap.
Architect and implement end-to-end ML systems (data → training → evaluation → deployment → monitoring) across vision, language, and retrieval domains
define rigorous offline and online evaluation frameworks, establish performance benchmarks, and implement feedback loops
develop reusable AI primitives, APIs, and shared services that reduce duplication and scale efficiently across the VERSANT portfolio
rigorously assess strengths, weaknesses, cost structures, and risk profiles, and guide teams in selecting the right solutions

What you’ll bring

All qualifications

Core experience

  • 8–12+ years of experience in machine learning, applied AI, and distributed systems, including significant experience operating models in production.
  • Deep expertise in Python and modern ML frameworks with strong software engineering fundamentals.
  • Demonstrated experience designing evaluation frameworks, monitoring strategies, and feedback loops for continuously improving model quality and safety.
  • Strong experience with large language models, retrieval systems, and generative AI, including real-world integration into applications.
  • Experience building or contributing to shared ML platforms, internal AI tooling, or reusable services used across multiple teams or business units.
  • Strong understanding of distributed systems, data engineering, cloud infrastructure (AWS, GCP, or Azure), and cost/performance trade-offs at scale.
Qualification wording
8–12+ years of experience in machine learning, applied AI, and distributed systems, including significant experience operating models in production.
Deep expertise in Python and modern ML frameworks with strong software engineering fundamentals.
Demonstrated experience designing evaluation frameworks, monitoring strategies, and feedback loops for continuously improving model quality and safety.
Strong experience with large language models, retrieval systems, and generative AI, including real-world integration into applications.
Experience building or contributing to shared ML platforms, internal AI tooling, or reusable services used across multiple teams or business units.
Strong understanding of distributed systems, data engineering, cloud infrastructure (AWS, GCP, or Azure), and cost/performance trade-offs at scale.
Apply at Versant

Posting record

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Status in our records
Live
First seen by us
Sep 25, 202641 days ago
Recorded sightings
145
Last seen by us
Nov 5, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$166K–$240K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 1,279 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 41

Similar jobs usually come down between day 6 and day 70.

Well past Versant’s usual: its jobs come down by about day 18.

From 4,523 similar postings that came down, and 75 of Versant’s. Coming down is not always a hire.

Versant is hiring

9 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring has slowed
  • Takes jobs down quickly
  • 56% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • AWS
  • Azure
  • GCP
Where the posting names them
- Proven track record of architecting and scaling end-to-end ML systems in high-traffic, production environments. - Deep expertise in Python and modern ML frameworks with strong software engineering fundamentals. - Demonstrated experience designing evaluation frameworks, monitoring strategies, and feedback loops for continuously improving model quality and safety.
- Experience building or contributing to shared ML platforms, internal AI tooling, or reusable services used across multiple teams or business units. - Strong understanding of distributed systems, data engineering, cloud infrastructure (AWS, GCP, or Azure), and cost/performance trade-offs at scale. - Experience partnering cross-functionally with product, engineering, and non-technical stakeholders; ability to influence senior leadership and translate ambiguity into execution.

Your next step

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Demand for ML Engineer roles

New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.

Weekly new ML Engineer postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 625, the most 1,094, and the latest week had 876.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

Job Description

We are seeking a Lead ML / AI Engineer to design and lead end-to-end ML/AI systems spanning computer vision, large language models, and retrieval-based architectures. You will build production-grade intelligence that powers products, operations, and newsroom workflows—while creating foundational AI capabilities that scale across the VERSANT portfolio. 

This role combines hands-on architecture with platform vision. You will guide model selection, experimentation, and integration into applications; establish rigorous standards for deployment and monitoring; and partner with Product, Engineering, Data, Executive Leadership, and Editorial teams to deliver high-impact systems. You will also mentor engineers and maintain a high bar for technical excellence across the ML lifecycle. 

Responsibilities 

  • Set the technical vision for ML/AI at VERSANT, translating business and newsroom priorities into a focused, high-impact execution roadmap. 

  • Architect and implement end-to-end ML systems (data → training → evaluation → deployment → monitoring) across vision, language, and retrieval domains, making high-leverage model and systems decisions that balance performance, latency, cost, and long-term maintainability at scale. 

  • Lead model evaluation and monitoring strategy: define rigorous offline and online evaluation frameworks, establish performance benchmarks, and implement feedback loops that continuously improve model quality, safety, and real-world impact. 

  • Develop deep expertise in the AI vendor landscape (foundation models, tooling, infrastructure providers), rigorously assess strengths, weaknesses, cost structures, and risk profiles, and guide teams in selecting the right solutions for their specific use cases. 

  • Identify cross-brand leverage points and develop reusable AI primitives, APIs, and shared services that reduce duplication and scale efficiently across the VERSANT portfolio. 

  • Partner directly with Editorial and product leaders to embed AI into newsroom workflows, content intelligence, and audience experiences. 

  • Partner closely with software engineering teams to ensure AI-powered applications are delivered with reliability, resiliency, and scalability as first-order requirements. 

Qualifications

Qualifications 

  • 8–12+ years of experience in machine learning, applied AI, and distributed systems, including significant experience operating models in production. 

  • Proven track record of architecting and scaling end-to-end ML systems in high-traffic, production environments. 

  • Deep expertise in Python and modern ML frameworks with strong software engineering fundamentals. 

  • Demonstrated experience designing evaluation frameworks, monitoring strategies, and feedback loops for continuously improving model quality and safety. 

  • Strong experience with large language models, retrieval systems, and generative AI, including real-world integration into applications. 

  • Experience building or contributing to shared ML platforms, internal AI tooling, or reusable services used across multiple teams or business units. 

  • Strong understanding of distributed systems, data engineering, cloud infrastructure (AWS, GCP, or Azure), and cost/performance trade-offs at scale. 

  • Experience partnering cross-functionally with product, engineering, and non-technical stakeholders; ability to influence senior leadership and translate ambiguity into execution. 

  • Experience in media, content, recommendation, search, or newsroom-adjacent systems is a strong plus. 

Additional Information

As part of our selection process, external candidates may be required to attend an in-person interview with a VERSANT Media employee at one of our locations prior to a hiring decision. VERSANT Media's policy is to provide equal employment opportunities to all applicants and employees without regard to race, color, religion, creed, gender, gender identity or expression, age, national origin or ancestry, citizenship, disability, sexual orientation, marital status, pregnancy, veteran status, membership in the uniformed services, genetic information, or any other basis protected by applicable law.

If you are a qualified individual with a disability or a disabled veteran and require support throughout the application and/or recruitment process as a result of your disability, you have the right to request a reasonable accommodation. You can submit your request to candidateaccessibility@versantmedia.com.

VERSANT Media is committed to fair and equitable compensation practices. We include a good faith pay range for each position to comply with applicable state and local pay transparency laws and to promote equity across our organization. Actual compensation will be based on factors such as the candidate's skills, qualifications, experience, and location and may include additional forms of compensation and benefits such as health insurance, retirement plans, paid time off, etc.

VERSANT Media is not accepting unsolicited assistance from search firms for this employment opportunity. All resumes submitted by search firms to any employee at VERSANT via-email, the Internet, or in any form and/or method without a valid written Statement of Work in place for this position from VERSANT's Talent Acquisition team will be deemed the sole property of VERSANT. No fee will be paid in the event the candidate is hired by VERSANT as a result of the referral or through other means.

Company Description

VERSANT (Nasdaq: VSNT) is an industry-changing media and entertainment business and home to trusted brands that shape culture, inform audiences, and build lasting connections. It operates across four core markets: political news and opinion, business news and personal finance, golf, and sports and genre entertainment. These markets are served through a powerful portfolio of iconic and innovative brands, including CNBC, MS NOW, USA Network, Golf Channel, Oxygen, E!, SYFY, and Versant's sports division USA Sports, along with complementary digital assets including Fandango, Rotten Tomatoes, GolfNow and GolfPass.

Source details

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Pay

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Location & working pattern

Englewood Cliffs, New Jersey, United States

Working pattern and location restrictions need checking in the full posting.

Work authorization
Additional Information As part of our selection process, external candidates may be required to attend an in-person interview with a VERSANT Media employee at one of our locations prior to a hiring decision. VERSANT Media's policy is to provide equal employment opportunities to all applicants and employees without regard to race, color, religion, creed, gender, gender identity or expression, age, national origin or ancestry, citizenship, disability, sexual orientation, marital status, pregnancy, veteran status, membership in the uniformed services, genetic information, or any other basis protected by applicable law. If you are a qualified individual with a disability or a disabled veteran and require support throughout the application and/or recruitment process as a result of your disability, you have the right to request a reasonable accommodation. You can submit your request to candidateaccessibility@versantmedia.com.

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