Software Engineer, Machine Learning

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

Improve model quality by refining thresholds, calibration, and guardrails to reduce false positives and decision noise

Build offline and online evaluation workflows tied to measurable business outcomes, enabling faster testing and more confident releases

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, including shipping model improvements safely and participating in the on-call rotation

Model quality improves on agreed business and operational metrics.

False positives,unstable decision behavior, and other secondary metrics are reduced in key flow.

Model testing/evaluation cycles become materially faster, better, and more performant.

More product testing and analysis

More model improvements reach production safely and predictably.

5+ years building ML models that were deployed and operated in production.

Extreme Proficiency in technical communication to nontechnical stakeholders.

Excellent applied ML fundamentals (classification/regression/forecasting + evaluation rigor)

Strong optimization understanding in business context

Strong Python and SQL with production engineering discipline (testing, maintainability, 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 large scale data processing and ML systems such as: Kedro, AutoGluon, PyTorch, Polars, BigQuery/GCP, Airflow/SQLMesh, and Databricks ecosystems.

Experience in Reinforcement Learning such as Q-Learning or Multi-Armed Bandits is a plus.

Our recruiters will always reach out using an email address ending with @mountain.com OR @mntn.com. If you’re contacted by someone without that address and they mention a Reference Code (which we never use), then that ain’t us folks. Tell those trolls to take a hike–you’re waiting to climb a MNTN.

MNTN provides advertising software for brands to reach their audience across Connected TV, web, and mobile. MNTN Performance TV has redefined what it means to advertise on television, transforming Connected TV into a direct-response, performance marketing channel. Our web retargeting has been leveraged by thousands of top brands for over a decade, driving billions of dollars in revenue.

Our solutions give advertisers total transparency and complete control over their campaigns all with the fastest go-live in the industry. As a result, thousands of top brands have partnered with MNTN, including Tarte, Decked, and National University.

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