Forbes Advisor
Department : Engineering
Company: Forbes Advisor
Jersey City, New Jersey | FULL_TIME |
Company Snapshot
Forbes Advisor helps people make informed decisions by providing trusted advice and guidance across various financial and lifestyle topics. This enables readers to confidently choose products and manage their finances. The company operates globally with experienced teams covering a wide range of consumer services, including credit, banking, investing, and insurance.
Role Overview / Mission
This role is for a Senior Machine Learning Engineer responsible for building, deploying, and maintaining production ML systems that support marketing optimization, forecasting, and automated decision-making across various business areas. The position involves managing the entire ML lifecycle, from data pipelines to model monitoring and improvement. This individual will collaborate with Data Science, Data Engineering, Business Intelligence, and Program Management teams. The role requires self-sufficiency, clear communication, and consistent delivery on multiple projects.
Key Responsibilities
* Design and operate ML pipelines in Google Cloud Platform (GCP), including data ingestion, feature engineering using BigQuery and dbt, and orchestration with Composer or Airflow for reproducible training.
* Develop and maintain low-latency model services and batch scoring jobs, ensuring robust continuous integration/continuous deployment (CI/CD), versioning, and rollback capabilities.
* Set up monitoring for model drift, data quality, and key business metrics, implementing alerts to prevent revenue loss and speed up issue resolution.
* Work with Data Science to transition models from development to production, covering models like propensity, customer lifetime value (LTV), churn prediction, and quality-weighted bidding.
* Partner with Marketing, Product, and Business Intelligence teams to integrate model outputs into campaigns, dashboards, and decision-making processes, including predictive optimization and Search Engine Marketing (SEM) auditing.
* Document technical contracts and metrics, enhance data layer alignment with Business Intelligence, and help standardize large-scale experimentation guidelines.
* Ensure the reliability, security, and cost-efficiency of ML systems.
Required Qualifications / Skills
* At least 5 years of experience in software or data engineering, with 3 or more years specifically focused on production ML systems.
* Proficiency in Python and SQL.
* Experience with ML libraries such as scikit-learn and either TensorFlow or PyTorch.
* Experience with Google Cloud Platform (GCP) tools including BigQuery, dbt, and Composer or Airflow.
* Familiarity with CI/CD practices and model serving frameworks or APIs.
* Practical experience with MLOps principles, including experiment tracking, model and data versioning, performance and drift monitoring, and incident response.
* Experience integrating model outputs into large-scale paid marketing or product workflows.
* Ability to manage multiple projects simultaneously, prioritize effectively, and communicate project status and technical trade-offs to both technical and non-technical stakeholders.
Preferred / Nice-to-Have Skills
* Experience with quality-weighted bidding, uplift modeling, or reinforcement learning-style policy optimization.
* Familiarity with Marketing Mix Modeling (MMM), Multi-Touch Attribution (MTA), and experiment design within marketing.
* Experience using Vertex AI or MLflow for model training and deployment.
* Skills in containerization and ensuring service reliability.
Location & Work Setup
This is a remote-first role with flexible working hours.
Compensation & Benefits
* Every third Friday off (monthly long weekends).
* Wellness stipend.
* Comprehensive parental leave policies.
Timezone: Europe/London
Posted: Sep 08, 2025
Expires: Oct 08, 2025