At Digital Turbine, we make mobile advertising experiences more meaningful and rewarding for users, app publishers, and advertisers - intelligently connecting people in more ways, across more devices. We provide app publishers and advertisers with powerful ads and experiences that captivate consumers, fuel performance, and help telecoms and OEMs supercharge awareness, acquisition, and monetization. In a rapidly evolving industry, we are constantly innovating and creating better paths of discovery to connect consumers, publishers, and advertisers across the mobile ecosystem.
The Team
The success of our business is greatly and directly influenced by our machine learning team. The team includes research, data science, statistical modeling and machine learning experts. The team's core objective is to automate decision making and increase its accuracy, by creating cutting edge models.
The Role
Senior Machine Learning Engineering Manager will be responsible for leading the data science, and ML engineering, and similar activities across our products developed in DT Warsaw Technology HUB. This role works closely with other engineers, data scientists and leaders in different locations to find innovative ways to apply emerging technologies to improve business processes and decision making, driving more value for our customers. The ideal candidate will have a strong background in machine learning model development, exploratory and predictive analytics which they can utilize to manage and improve our company's AI and ML initiatives.
Duties and responsibilities

• Build and manage a world class team of data scientists, and data engineers
• Guide the team to architect an entire AI and ML engineering platform that allows for deployment and scalability of machine learning models
• Build the tools and capabilities for model management and model performance monitoring
• Guide the team to operating services at internet scale with high availability and reliability
• Propose and implement the best engineering and research practices for scaling ML powered features, with a goal to enable the fast iteration of and efficient experimentation with a novel features
• Contribute to and influence the ML infrastructure roadmap based on the feedback from internal stakeholders

Skills and experience

• 5+ years of experience in machine learning
• 2+ years of experience in a leadership role
• Experience and understanding of the entire machine learning pipeline from data ingestion to production
• Experience in machine learning operations, software engineering and architecture
• Experience in a large-scale systems including parallel computing
• Experience architecting and building a platform that supports productionization of ML models
• Experience with MLOps systems
• Strong programming skills in a scientific computing languages (i.e. Python)
• Experience using frameworks for machine learning and data science (i.e. pandas, NumPy)
• Experience working with ML tools (i.e. Tensorflow, PyTorch)
• Ability to take successful, complex research ideas from experimentation to production
• Excellent written and oral communication skills and the capability to drive cross-functional requirements with product and engineering teams

About Digital Turbine:
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 the ability to supercharge awareness, acquisition and monetization - connecting our partners to more consumers, in more ways, across more devices.
The company is headquartered in Austin, Texas, with global offices in New York, Los Angeles, San Francisco, London, Berlin, Singapore, Tel Aviv, and other cities serving top agency, app developer, and advertising markets. Listed on Deloitte Technology Fast 500 for six consecutive years since 2015 and winner of Austin Chamber of Commerce's Company Culture in 2020.
Digital Turbine is an equal opportunity employer committed to building a diverse and inclusive team. We welcome people of different backgrounds, experiences, abilities, and perspectives. We embed diversity in our mindset, products, and teams to empower an inclusive, equitable, and culturally fluent environment. Building this culture within our teams makes us better collaborators and partners, driving better outcomes.
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