{"id":474472,"url":"https://alion.io/job/digital-turbine-senior-machine-learning-engineer","title":"Senior Machine Learning Engineer","company":{"id":179744,"name":"Digital Turbine","domain":"digitalturbine.com","url":"https://alion.io/company/digital-turbine","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":174000,"max_usd":335000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1332},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"C++","optional":false},{"name":"Feature Store","optional":false},{"name":"Flink","optional":false},{"name":"Java","optional":false},{"name":"JAX","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Recommender Systems","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"TensorFlow","optional":false},{"name":"TensorFlow C++","optional":false},{"name":"AI Agents","optional":true},{"name":"Databricks","optional":true}],"status":"live","first_seen_at":"2026-08-13T00:00:00Z","employer_posted_date":"2026-10-12","last_verified_at":"2026-11-01T10:11:02Z","board_verified":true,"closed_at":null,"days_open":80,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":80},"description":"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.\nAt 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.\nHere, you’ll have the opportunity to grow your career while contributing to products and experiences used by millions around the world.\nWith 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.\nThe Role\nDT 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).\nAs 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.\nWhat you'll do\nDesign, build, and deploy large-scale ML systems for ad ranking, click-through and conversion prediction, bid optimization, and next-best-action recommendation.\n\nBuild and operate production ML pipelines - feature engineering, distributed training, deployment, retraining, and monitoring - that process billions of events and serve predictions at low latency.\n\nLeverage 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.\n\nOptimize training and inference for compute efficiency (CPU/GPU utilization), latency, and cost across distributed systems.\n\nPartner 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.\n\nStay current with applied ML research and bring innovative techniques to advertising, ranking, and audience modeling.\n\nWhat you'll bring\n8+ years building and deploying ML systems in production at scale, ideally in AdTech, recommender systems, search/ranking, or real-time bidding.\n\nStrong software-engineering fundamentals - data structures, algorithms, system design - and proficiency in Python (plus Java, Scala, or C++ a strong plus).\n\nHands-on experience with modern ML frameworks (PyTorch, TensorFlow, or JAX) and distributed data/compute systems (Spark, Beam/Dataflow, Flink, or similar).\n\nExperience building robust ML pipelines: feature stores, data versioning, model monitoring, and automated retraining.\n\nA record of shipping models that demonstrably improved product or business metrics (e.g., CTR, CVR, ROAS).\n\nMaster's or Ph.D. in CS, ML, or a related field, or equivalent practical experience.\n\nNice to have\nExperience with real-time, low-latency model serving and online learning.\n\nFamiliarity with Databricks / Unity Catalog, semantic layers, or feature platforms.\n\nExperience with LLMs and agentic systems applied to audience insight or optimization.\n\nDT (NASDAQ: APPS) is a mobile growth platform that powers superior experiences and outcomes for advertisers, app developers, carriers, OEMs, and publishers worldwide.\nOur 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.\nHeadquartered in Austin, Texas, DT operates globally across North America, EMEA, APAC, and LATAM.\nDT is an equal opportunity employer committed to fostering an inclusive and diverse workplace. 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