Enable job alerts via email!

Product Manager - MLOps Platform (Contract)

Searchability

United Kingdom

Remote

GBP 70,000 - 90,000

Full time

Yesterday
Be an early applicant

Job summary

A tech-focused recruitment agency is looking for an experienced MLOps Product Owner to lead the development of a greenfield MLOps platform. The ideal candidate has over 5 years in product management and at least 2 years in AdTech or digital media. This fully remote role offers a unique opportunity to shape the architecture of ML use cases in the advertising sector.

Qualifications

  • 5+ years of product management experience, ideally in AdTech or digital media.
  • Experience building ML platforms or infrastructure in cloud environments.
  • Strong understanding of programmatic advertising and campaign measurement.

Responsibilities

  • Lead end-to-end development of the MLOps platform.
  • Collaborate with cross-functional teams to identify automation opportunities.
  • Manage delivery using agile methodologies.
  • Drive platform adoption through best practices in ML operations.

Skills

Product management
Communication skills
Stakeholder management
Agile methodologies

Tools

GCP
BigQuery
Vertex AI
Dataflow
Airflow
dbt

Job description

MLOps Product Owner (Contract)

  • Location: Remote UK
  • Clearance: Must be eligible for BPSS
  • Stance: Inside IR35

We’re looking for a forward-thinking Product Manager to lead the end-to-end development of a greenfield MLOps platform tailored for the fast-paced and data-intensive world of AdTech. This is a unique opportunity to architect a foundational capability that will power advanced Machine Learning use cases across our advertising ecosystem.

Responsibilities:

  • Work closely with data science, engineering, analytics, and AdOps teams to understand current workflows and identify opportunities to streamline and automate the ML lifecycle.
  • Assess existing data, analytics, and infrastructure frameworks to identify reusable components and define the architectural blueprint for the MLOps platform.
  • Collaborate with backend and platform engineering teams to identify technical gaps, scope backend development efforts, and deliver core platform capabilities such as:
  • Model training orchestration
  • CI/CD for ML (e.g., using MLflow, Kubeflow, or Vertex AI Pipelines)
  • Model versioning, monitoring, and governance
  • Enable high-impact AdTech use cases including:
  • Marketing Mix Modeling (MMM)
  • Real-time personalization and bidding
  • Audience segmentation and targeting
  • Predictive analytics for campaign performance
  • Ensure seamless integration with Order Management Systems (OMS), Customer Data Platforms (CDPs), Data Warehouses (e.g., BigQuery), and custom BI tools to support real-time and batch model consumption.
  • Translate business needs into detailed product requirements, user stories, and technical specifications, and manage delivery using agile methodologies.
  • Drive platform adoption by evangelizing best practices in ML operations, model governance, and responsible AI.

Required Experience:

  • 5+ years of product management experience, with at least 2 years in AdTech, MarTech, or digital media platforms.
  • Proven experience building ML platforms or infrastructure from scratch, ideally in a cloud-native environment.
  • Strong understanding of programmatic advertising, attribution modeling, campaign measurement, and media mix optimization.
  • Familiarity with cloud platforms (especially GCP) and tools like BigQuery, Vertex AI, Dataflow, Airflow, and dbt.
  • Excellent communication and stakeholder management skills, with the ability to align cross-functional teams around a shared vision

To be Considered:

Please either apply through this advert or email me directly vialewis.hayward@searchability.com. For further information, call me on0117 284 0050 / 07719 072 818. By applying for this role, you give express consent for us to process and submit (subject to required skills) your application to our client in conjunction with this vacancy only.

Get your free, confidential resume review.
or drag and drop a PDF, DOC, DOCX, ODT, or PAGES file up to 5MB.