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tvScientific

Machine Learning Systems Engineer

Posted 10 Hours Ago
Be an Early Applicant
Remote
Hiring Remotely in USA
125K-165K
Entry level
Remote
Hiring Remotely in USA
125K-165K
Entry level
As an ML Systems Engineer, you will develop and manage ML models, improve inference speed, and design ML products for CTV advertising.
The summary above was generated by AI

Job Title: ML Systems Engineer
Location: Remote, US
Department: Data Science 
Type: Full-Time, Exempt
Experience: New Grad / Early Career (0-3 Years)
Salary Range: $125,000 - $165,000 base
Core Hours: 9 AM - 1 PM PST / 12 - 4 PM EST


About tvScientific

tvScientific is the first and only CTV advertising platform purpose-built for performance marketers. We leverage massive data and cutting-edge science to automate and optimize TV advertising to drive business outcomes. Our solution combines media buying, optimization, measurement, and attribution in one, efficient platform. Our platform is built by industry leaders with a long history in programmatic advertising, digital media, and ad verification who have now purpose-built a CTV performance platform advertisers can trust to grow their business.


Role Summary

tvScientific is looking for a ML Systems Engineer with experience in Zig to join our growing team! You'll be working with a distributed engineering team on our Connected TV ad-buying platform, as we scale our Data Science practice from zero to one. We’re building data science tools for constructing ad campaigns from content to timing to scheduling to bid optimization.

Our self-managed platform makes it easy to buy, optimize, and prove the value of TV advertising. An Idealab company, tvScientific was co-founded by executives with deep roots in programmatic advertising and digital media. tvScientific helps our clients buy ads across the CTV universe, from Hulu to PlutoTV to the ad-supported tier of Disney+ and (HBO) Max. We have a new partnership with Roku to advance CTV performance advertising.


What You'll Do

  • Write production code in Zig
  • Train, deploy, and manage new ML models for ads in CTV
  • Improve the speed of tvScientific's ML inference at scale
  • Plan and design new ML products to deliver clear performance from connected TV advertising

You’ll Be Successful in This Role if You Have/Are

  • Excellent writing skills
  • Strong understanding of computer systems
  • Desire to work at a fast-growing Series B startup–working under uncertainty, owning and scaling new products, and an experimental and iterative development process

You May Also Have

  • Adtech or CTV experience
  • Experience working with systems requiring low latency (<10 ms)
  • Teaching experience
  • Big data experience with Scala, Apache Spark, Apache Beam, and AWS Athena
  • Python and ML experience
  • Kubernetes/EKS experience


Culture and Benefits

At tvScientific we believe people do their best work when they feel challenged and engaged by their day to day responsibilities, when they’re surrounded by smart, hard working people, and when they have a healthy work life balance. Our company culture and benefits package reflects these beliefs.

  • Full health, dental, and vision insurance - up to 95% funded by the company for employees.
  • Employee stock option program.
  • Company-sponsored retirement plan with a matching contribution program.
  • 12 annual paid holidays (including 2 flexible days).
  • Generous PTO policy (get your work done and take the time you need).
  • A remote-first environment that allows employees flexibility to work from most places in the US.


tvScientific is committed to building an inclusive environment for people of all backgrounds and everyone is encouraged to apply. tvScientific is an Equal Opportunity Employer and does not discriminate on the basis of race, color, gender, sexual orientation, gender identity or expression, religion, disability, national origin, protected veteran status, age, or any other status protected by applicable national, federal, state, or local law.

Top Skills

Apache Beam
Spark
Aws Athena
Eks
Kubernetes
Python
Scala
Zig

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