Software Engineer, Machine Learning
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Job Description
Machine learning engineer operationalizing scalable production models for MNTN’s Connected TV advertising platform. Building reliable ML systems that optimize campaigns for brands.
Responsibilities:
- Design and build a robust marketing platform that reaches the right audience, anywhere and anytime
- Build high-volume services that remain reliable at scale
- Develop 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 Leads, and platform-focused Machine Learning and Data Engineers to improve service reliability, latency, observability, and data freshness
- Share ownership of production systems, ship model improvements safely, and participate in the on-call rotation
- Operationalize data scientist prototypes into robust, scalable production systems
- Lead deployment, monitoring, and maintenance of machine learning solutions powering campaign optimizations at scale
Requirements:
- 5+ years building ML models deployed and operated in production
- Extreme proficiency in technical communication to nontechnical stakeholders
- Excellent applied ML fundamentals, including classification, regression, forecasting, and rigorous evaluation
- Strong understanding of optimization in a business context
- Strong Python and SQL skills with production engineering discipline, including testing, maintainability, and performance
- Experience balancing model quality, system constraints, and speed-to-production
- Strong experience with ownership and cross-functional collaboration
- Experience in ad tech, growth analytics, personalization, or performance marketing
- Proficiency working with real-time or near-real-time data pipelines
- Experience with experimentation frameworks and production model monitoring
- Experience with large-scale data processing and ML systems such as Kedro, AutoGluon, PyTorch, Polars, BigQuery/GCP, Airflow/SQLMesh, and Databricks ecosystems
- Reinforcement Learning experience such as Q-Learning or Multi-Armed Bandits is a plus
Benefits:
- People-first company culture
- Named one of Ad Age’s Best Places To Work in 2026
- Remote work arrangement
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