Senior Machine Learning Engineer
SW5 Consulting
Production ML & Vertex AI (GCP)Data Engineering & Feature PipelinesExperience in AdTech, Ecommerce attribution, or Marketing Automation.
Role Overview
We are looking for a Senior Machine Learning Engineer who goes beyond simply training models. You will be responsible for the end-to-end lifecycle of production-grade decisioning systems. This role is ideal for a proactive engineer who thrives in a startup environment, owning everything from data contracts and feature pipelines to deployment, monitoring, and iteration. You will bridge the gap between high-level research and robust production engineering, ensuring our models drive real business lift under complex real-world constraints.
Key Responsibilities
- Full-Cycle Ownership: Own the entire ML lifecycle including data contracts, feature engineering, training, evaluation, deployment, and monitoring.
- Productionize ML: Build and maintain production-grade decisioning systems within GCP/Vertex AI, ensuring high availability and performance.
- Data Engineering: Define feature definitions and backfills, ensuring offline/online parity and managing drift monitoring.
- Cross-functional Collaboration: Partner with Product and Customer Success teams to translate business requirements into technical policies and constraints.
- Advanced Modeling: Handle complex data challenges such as delayed/biased labels, attribution windows, and censored data.
Required Qualifications
- Proven experience shipping end-to-end decisioning systems (not just model deployment) under production constraints.
- Expertise in Google Cloud Platform (GCP) and Vertex AI.
- Strong experience with BigQuery and handling large-scale data environments.
- Deep understanding of the research-to-production pipeline: policy, constraints, and measurement.
- Experience working with biased labels, attribution windows, or missing-not-at-random data.
Preferred Qualifications
- Experience in AdTech, Ecommerce attribution, or Marketing Automation.
- Knowledge of Bandit algorithms, causal modeling, or uplift modeling.
- Experience with PyTorch, Transformer models, and LLM implementations.
- Familiarity with Airflow for orchestration.