19 hours ago
Responsibilities
- Design and build a robust marketing platform for audience targeting across channels.
- Build reliable high-volume services and big data solutions using open-source frameworks.
- Design, train, evaluate, and improve models for deliverability, forecasting, and optimization.
- Refine thresholds, calibration, and guardrails to reduce false positives and decision noise.
- Build offline and online evaluation workflows tied to measurable business outcomes.
- Partner with product, project, machine learning, and data engineering teams to improve reliability, latency, observability, and data freshness.
- Own production systems, safely ship model improvements, and participate in the on-call rotation.
Requirements
- At least 5 years of experience building machine learning models deployed and operated in production.
- Strong applied machine learning fundamentals, including classification, regression, forecasting, and rigorous evaluation.
- Strong Python and SQL skills with production engineering discipline around testing, maintainability, and performance.
- Strong understanding of optimization in a business context and the ability to balance model quality, system constraints, and speed to production.
- Experience with real-time or near-real-time data pipelines, experimentation frameworks, and production model monitoring.
- Experience with large-scale data processing and machine learning systems such as Kedro, AutoGluon, PyTorch, Polars, BigQuery/GCP, Airflow/SQLMesh, and Databricks ecosystems.
- Experience in ad tech, growth analytics, personalization, or performance marketing.
- Excellent technical communication with nontechnical stakeholders and strong cross-functional ownership.
- Experience with reinforcement learning, such as Q-Learning or Multi-Armed Bandits, is preferred.
Benefits
- Remote work is indicated by the #LI-Remote designation.
Tech Stack
Categories
About MNTN
MNTN builds a self-serve Connected TV advertising platform that lets brands and agencies run performance-focused TV campaigns with attribution, retargeting, and prospecting. Its core product, Performance TV, ties conversions and revenue back to TV ad spend to support direct-response goals. Founded in 2018 and headquartered in Austin with a remote workforce, the company is privately held.