Product Manager CGEMJP00300105

Experis; United Kingdom; Remote; GBP 70,000 - 90,000; Full time

Job summary

A leading tech consultancy is seeking a Product Manager MLOps Platform with a focus on AdTech. You will lead the development of a greenfield MLOps platform, collaborating with data science and engineering teams to implement scalable ML solutions. The ideal candidate has over 5 years of product management experience with a strong background in AdTech and cloud-native environments. This remote position offers the opportunity to work on cutting-edge ML projects.

Qualifications

• 5+ years of product management experience, at least 2 years in AdTech.
• Experience building ML platforms or infrastructure from scratch.
• Understanding of programmatic advertising and campaign measurement.

Responsibilities

• Lead the development of MLOps platform for AdTech.
• Collaborate with engineering and analytics teams.
• Translate business needs into product requirements.

Skills

Product vision ownership

Data science collaboration

ML lifecycle automation

Agile methodologies

Stakeholder management

Tools

MLflow

Kubeflow

Vertex AI

BigQuery

Dataflow

Airflow

dbt

Job description

Social network you want to login/join with:

Location: England Job Type: Contract Industry: Business Transformation Job reference: BBBH418050_1753089514 Posted: 2 days ago

Role Title: Product Manager MLOps Platform (AdTech Focus)

Duration: 5 months from start date

Location: Remote

Role purpose / summary

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.

Key Skills/ requirements

Define and own the product vision and roadmap for a brand-new MLOps platform, built from the ground up to support scalable, secure, and efficient ML model development, deployment, and monitoring.

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.

Preferred Qualifications:

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

All profiles will be reviewed against the required skills and experience. Due to the high number of applications we will only be able to respond to successful applicants in the first instance. We thank you for your interest and the time taken to apply!