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 • 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. 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.

Requirements

Must-haves

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

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

mlaimachine learningpythonawsgcpazure

Platform: smartrecruiters
Effort: medium

Benefits

Benefits detected in the listing.

Health Insurance

Vision

Paid Time Off