At MNTN, we put our people first, full stop. This allows our company culture to be defined by our team members, and their shared values, like trust, ambition, quality, radical honesty, and compassionate leadership. It’s why we all really love working for the Hardest Working Software in Television™ (and also why we were named one of Ad Age’s Best Places To Work in 2024.)
We pride ourselves on bringing unrivaled performance and simplicity to Connected TV advertising. Our self-serve technology makes running TV ads as easy as search and social and helps brands drive measurable conversions, revenue, site visits, and more. It’s what led MNTN to being named one of Fast Company's Most Innovative Companies in 2023. You can learn more about us and everything we do by visiting https://mountain.com/.
So if wanting to do more, own more, and make a bigger impact comes naturally to you, then you may just the person we're looking for to join us on our next stage of growth.
As a Senior Machine Learning Engineer on our ML Squad, you will ideate, train, test, deploy, evaluate and monitor matching systems in a large scale production environment to maximize advertiser goals while respecting consumer privacy. As a core contributor to how we best match ads, you will work with data science, software engineers, product managers, infrastructure teams, and data teams. Relevant experience includes propensity modeling, ranking, predictive modeling, spam detection, clustering, segmentation, and similar.
What You’ll Do:
- Use MNTN proprietary and third party data sources to conceive and lead machine learning projects that maximize goals for advertising marketers while protecting consumer privacy.
- Be a hands-on builder of needed components in software and infrastructure.
- Become the end to end expert on matching ad opportunities to potential audiences in an ambiguous and privacy-focused ecosphere.
- Identify opportunities and gaps in data and insights for both internal and external stakeholders.
- Work with product and engineering teams to create and evaluate your model designs.
- Lead discussions with other technical and non-technical functions.
- Investigate critical incidents and provide insights to data ambiguity.
What You’ll Bring:
- 5+ years of experience of real-world problem solving related to developing and using machine learning models on large scale data. Advanced degrees in Computer Science, Mathematics, Electrical Engineering, Statistics or similar may be substituted for some years of experience.
- Experience in SQL, Python, Spark, R, or similar languages.
- Experience in machine learning libraries and platforms such as scikit-learn, tensorflow, sagemaker, or similar.
- Written and verbal communication skills to convey complex technical topics to a variety of audiences.
MNTN perks:
- Work from home anywhere in the U.S.
- Flexible vacation policy
- Annual vacation allowance for travel related expenses
- Three-day weekend every month of the year
- Competitive compensation
- 100% healthcare coverage
- 401k plan
- Flexible Spending Account (FSA) for dependent, medical, and dental care
- Access to coaching, therapy, and professional development
About MNTN:
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, Build with Ferguson, Tarte, OneWheel, Decked, and National University.
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