Senior Machine Learning Engineer

Posted 2 Months Ago
New York, NY, USA
In-Office
Senior level
AdTech
Awarded Best Places to Work in Austin, Los Angeles, New York, San Francisco, Seattle and Washington DC by Built In!
The Role
Design, build, and deploy large-scale ML systems for ad ranking, bid optimization, and recommendations. Build and operate production ML pipelines (feature engineering, distributed training, deployment, retraining, monitoring) that process billions of events and serve low-latency predictions. Optimize training and inference for compute and cost efficiency. Partner with Data Science, Data Engineering, and product teams to ship models, run online experiments, and measure CTR/CVR/ROI impact. Incorporate applied ML research and techniques into advertising and audience modeling.
Summary Generated by Built In

DT (NASDAQ: APPS) is unifying the full mobile experience. Our growth platform powers the mobile ecosystem by bringing together advertisers, app developers, and device partners, to create a unique and premium value exchange, that results in a personalized and seamless mobile device experience.


At DT, we move fast, think big, and build collaboratively. We believe great ideas can come from anywhere, and we trust our teams to take ownership, challenge convention, and make an impact from day one.


Here, you’ll have the opportunity to grow your career while contributing to products and experiences used by millions around the world.

With us, you will enjoy competitive compensation, equity awards, and a comprehensive benefits package designed to invest in your total well-being, all within a hybrid and flexible work environment.

The Role
 

DT is transforming from a distribution company into a data-intelligence company. At the center of that shift is our ML platform and the "Next Best Action" framework — the capability that lets every DT product activate user-level models in real time against our unified, first-party device-level data (the DT User Card).

As a Senior Machine Learning Engineer, you'll design and scale the ML systems behind ad ranking, bid optimization, recommendation, and user-level prediction across our demand and supply businesses — the DSP, offer wall, content media, notifications, and Ignite. You'll build the pipelines and serving infrastructure that turn our data advantage into measurable lifts in CTR, CVR, and ROI, and help DT show up as an AI-first company.


What you'll do
  • Design, build, and deploy large-scale ML systems for ad ranking, click-through and conversion prediction, bid optimization, and next-best-action recommendation.

  • Build and operate production ML pipelines — feature engineering, distributed training, deployment, retraining, and monitoring — that process billions of events and serve predictions at low latency.

  • Leverage the data assets from across the DT product portfolio to enable ML solutions that create decisioning in real time using the entire breadth of available features.

  • Optimize training and inference for compute efficiency (CPU/GPU utilization), latency, and cost across distributed systems.

  • Partner closely with Data Science, Data Engineering, and product teams to ship models that move key business metrics, and run rigorous online experiments to validate impact.

  • Stay current with applied ML research and bring innovative techniques to advertising, ranking, and audience modeling.


What you'll bring
  • 8+ years building and deploying ML systems in production at scale, ideally in AdTech, recommender systems, search/ranking, or real-time bidding.

  • Strong software-engineering fundamentals — data structures, algorithms, system design — and proficiency in Python (plus Java, Scala, or C++ a strong plus).

  • Hands-on experience with modern ML frameworks (PyTorch, TensorFlow, or JAX) and distributed data/compute systems (Spark, Beam/Dataflow, Flink, or similar).

  • Experience building robust ML pipelines: feature stores, data versioning, model monitoring, and automated retraining.

  • A record of shipping models that demonstrably improved product or business metrics (e.g., CTR, CVR, ROAS).

  • Master's or Ph.D. in CS, ML, or a related field, or equivalent practical experience.


Nice to have
  • Experience with real-time, low-latency model serving and online learning.

  • Familiarity with Databricks / Unity Catalog, semantic layers, or feature platforms.

  • Experience with LLMs and agentic systems applied to audience insight or optimization.

DT (NASDAQ: APPS) is a mobile growth platform that powers superior experiences and outcomes for advertisers, app developers, carriers, OEMs, and publishers worldwide.


Our technology connects brands and apps with consumers across devices, apps, and mobile environments — helping partners drive awareness, acquisition, engagement, and monetization through intelligent, integrated experiences.


Headquartered in Austin, Texas, DT operates globally across North America, EMEA, APAC, and LATAM.


DT is an equal opportunity employer committed to fostering an inclusive and diverse workplace. We welcome people of different backgrounds, experiences, abilities, and perspectives, and believe teams with different points of view build better products, ideas, and experiences.

Skills Required

  • 8+ years building and deploying ML systems in production at scale, ideally in AdTech, recommender systems, search/ranking, or real-time bidding.
  • Strong software-engineering fundamentals including data structures, algorithms, and system design.
  • Proficiency in Python.
  • Proficiency in Java, Scala, or C++.
  • Hands-on experience with modern ML frameworks (PyTorch, TensorFlow, or JAX).
  • Experience with distributed data/compute systems (Spark, Beam/Dataflow, Flink, or similar).
  • Experience building robust ML pipelines: feature stores, data versioning, model monitoring, and automated retraining.
  • Proven record of shipping models that demonstrably improved product or business metrics (e.g., CTR, CVR, ROAS).
  • Master's or Ph.D. in CS, ML, or a related field, or equivalent practical experience.
  • Hybrid work environment — candidates local to the posting location only.
  • Experience with real-time, low-latency model serving and online learning.
  • Familiarity with Databricks, Unity Catalog, semantic layers, or feature platforms.
  • Experience with LLMs and agentic systems applied to audience insight or optimization.

Digital Turbine Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Digital Turbine and has not been reviewed or approved by Digital Turbine.

  • Healthcare Strength — Healthcare coverage is positioned as comprehensive, spanning medical, dental, and vision alongside life and travel insurance. Fully paid short-term disability is also presented as a meaningful safety-net benefit.
  • Equity Value & Accessibility — Equity is framed as broadly accessible, with stock/equity included for employees at hire and additional grants tied to performance. This structure can materially increase total rewards for those who value ownership and participate over time.
  • Leave & Time Off Breadth — Time-off and flexibility offerings are presented as expansive, including unlimited vacation, flexible hours, and supportive leave policies. Paid parental leave is highlighted as part of a broader leave package.

Digital Turbine Insights

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The Company
HQ: Austin, TX
950 Employees
Year Founded: 1998

What We Do

Digital Turbine (NASDAQ: APPS) powers superior mobile consumer experiences and results for the world's leading telcos, advertisers, and publishers. Our end-to-end platform uniquely simplifies our partners' ability to supercharge their awareness, acquisition, and monetization — connecting them with more consumers, in more ways, across more devices. Digital Turbine is headquartered in North America, with offices around the world. For more about Digital Turbine: www.digitalturbine.com

Why Work With Us

Everyone’s empowered to “Work their Way," while global mindsets & diverse perspectives are celebrated daily. We work hard, but also take time to enjoy the journey, and have fun while doing it. Our team is down to earth and supportive, which is needed in our fast-paced mobile ad technology space.

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